Abstract The National Cancer Institute’s Patient Derived Models Repository (NCI PDMR; https://pdmr.cancer.gov) has developed a national repository of Patient-Derived Models (PDMs) currently comprised of over 1000 patient-derived xenograft (PDX), 450 organoid (PDOrg), 500 tumor cell culture (PDC), and 425 cancer associated fibroblast (CAF) models. Over 450 PDXs have matched PDOrg and/or PDCs allowing for complimentary/parallel in vivo/in vitro studies. These PDMs are clinically annotated with molecular information available in a public database for the extramural community with additional molecular features including OncoKB annotated mutations, microsatellite instability (MSI), human leukocyte antigen (HLA) typing, and clinically relevant fusions. Researchers can use these clinical and molecular features or perform their own independent analyses using the public data to aid in their selection of preclinical models. Due to the large number of NCI PDMR models within histologies and research community interest, we have developed histology-based PDX TMAs to further facilitate the selection of models for cancer research. Each TMA panel includes up to 60 unique PDX models, with two 1.5mm cores/model plus murine control tissue. Quality control (QC) assessment of the TMA cores is performed by a pathologist. Each core is reviewed with an initial pass/fail threshold set to ≥10% human tumor/core area with ≥500 tumor cells. TMA slides pass QC if they meet these criteria and ≥75% of the models have at least one passing core. TMA blocks are QC’d at regularly set intervals to ensure all distributable slides meet these requirements. The first PDX TMA panel available for distribution this year (PANC I) contains 60 pancreatic cancer PDXs (predominantly pancreatic adenocarcinoma [PAAD]) derived from primary and metastatic lesions from treatment naïve through heavily pretreated patients. KRAS mutated models include 28 G12D, 15 G12V, 10 G12R, 3 G12C, 1 Q61H, and 3 KRAS wildtype. Other genes frequently mutated in pancreatic cancer are also found in this cohort including TP53, SMAD4, and CDKN2A. Also in development are four colorectal cancer TMAs panels: (1) a general set of colon adenocarcinomas (COAD) with features including early onset, non-European ancestry, and MSI-High; (2) KRAS mutated COAD; (3) Treatment naïve COAD and wildtype APC COAD; and (4) Rectal adenocarcinoma models. These TMAs can be used to stratify models by therapeutic target, develop predictive markers or classify differential signaling in disease subtypes, integrative analysis of genomic and protein expression, and discover or validate biomarkers of disease in an efficient and cost-effective way. Targeted model selection is of high importance to better understand the biology of these cancers and improve preclinical drug testing and screening design to translate novel therapeutics from bench to clinic. Citation Format: Cindy R. Timme, Lindsay Dutko, Sayak Ghatak, Ting-Chia Chang, Alice P. Chen, Li Chen, Biswajit Das, Tara Grinnage-Pulley, Shahanawaz Jiwani, Kaci Paulus, Chris A. Karlovich, Sergio Alcoser, Yvonne Evrard, Melinda G. Hollinghead, James H. Doroshow. Development of pancreatic and colon patient-derived xenograft (PDX) tumor microarrays (TMAs) from the NCI patient derived models repository [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 6061.

Abstract Head and neck (HN) cancers are a rare set of cancers defined by their anatomical point of origin including mouth, sinus, throat, or nose. Human papilloma virus (HPV) infection plays a pathogenic role in HN cancers resulting in distinct clinical and molecular characteristics from those that are HPV-. The National Cancer Institute’s Patient-Derived Models Repository (NCI PDMR; https://pdmr.cancer.gov) has developed a national repository of patient-derived models (PDMs) comprised of patient-derived xenografts (PDXs), organoids (PDOrg), tumor cell cultures (PDCs) and cancer associated fibroblasts (CAFs). These models are clinically annotated with molecular information available in a public database for the extramural community. To date, 361 patient HN tumor specimens have been received from 351 unique patients across a range of histologies including lip/oral, pharyngeal, laryngeal, salivary and sinonasal with an overall PDX take rate of 48% (322 assessable specimens). The NCI PDMR currently has 200 public HN PDX, PDOrg, and PDC models from 124 unique patients. Thirty-three models (PDX, PDOrg, PDC) from 20 unique patients are positive for HPV16 or 18 (one double positive) as detected by PCR and one sinonasal PDOrg model is positive for HPV33 identified in NextGenSeq data. As has been reported in the clinical literature, TP53 and CDKN2A mutations are found predominantly in PDX models that are HPV- (84% and 65%, respectively) but not HPV+ (0%; 0%) and PIK3CA is more commonly mutated in HPV+ models (47% vs 25%). No significant difference in loss of heterozygosity is observed in the models. However, significant differences in chromosome arm copy number changes (copy gains in 7p, 11p and 12p and copy losses in 3p, 9p and 18q [P-value<0.05; Wilcoxon Rank-Sum test]) are observed in HPV- compared to HPV+ models. Gene set enrichment analysis (GSEA) suggest the E2F_TARGETS, G2M_CHECKPOINT, and DNA_REPAIR gene sets are significantly up-regulated in HPV+ while the APOPTOSIS gene set is significantly down-regulated using MSigDB Hallmark dataset (P-value<0.05). In all analyses, differences are consistent whether examining in vivo PDX models or in vitro PDC/PDOrg models indicating the fidelity of the models. These preclinical models recapitulate the molecular differences reported in HPV+ versus HPV- clinical cases providing an important tool for the development of novel therapeutics for HN cancers. Funded by NCI Contract No. HHSN261200800001E Citation Format: Yvonne A. Evrard, Ting-Chia Chang, Jasmine B'Lanton, Gareth Bliss, Alice Chen, Li Chen, Kevin Cooper, Kristin Cox, Natalie Czarra, Isabella Czernia, Biswajit Das, Kelly Dougherty, Aarin Dreyer, Lindsay Dutko, Katie Frey, Marion Gibson, Tara Grinnage-Pulley, Shahanawaz Jiwani, Poorva Juneja, Keegan Kalmbach, Tamikia Lamb, Eva Loewenstein, Candace Mallow, Chelsea McGlynn, Justine Mills, Michael Mullendore, Matthew Murphy, Sandra Navas-Reyes, Michelle Norris, Jessica Park, Kaci Paulus, Kevin Plater, Tia Shearer, Jessica Steed, Luke Stockwin, Howard Stotler, Ruth Thornton, Cindy R. Timme, Shannon Uzelac, Dianne L. Newton, Chris A. Karlovich, Melinda G. Hollingshead, James H. Doroshow. HPV+ and HPV- head and neck cancer patient-derived models in the NCI Patient-Derived Models Repository [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 6067.

3045 Background: In the NCI-MATCH trial (NCT02465060), tumor tissue from 5,954 patients with advanced cancers underwent next-generation sequencing using the Oncomine Comprehensive Assay v2 (OCAv2) to determine eligibility. Most tumors lacked a qualifying mutation of interest (MOI) for assignment. Plasma from 1,301 patients with common cancers – [colorectal (COADREAD), breast (BREAST), non–small cell lung (NSCLC), and prostate (PRAD) (OncoTree codes are shown in parentheses)] was analyzed to characterize circulating tumor DNA (ctDNA) and assess its utility for detecting clinically relevant MOIs. Methods: Cell-free DNA was extracted from plasma collected in Streck tubes at enrollment. ctDNA profiling was performed using the NCI ctDNA Research v2 assay (523 genes) on the Illumina NovaSeq 6000. Matched tumor tissue was analyzed using OCAv2 (143 genes). Positive percent agreement (PPA) was calculated using tissue as the reference. Blood-based microsatellite instability (bMSI) was assessed across ~2,400 loci, with bMSI-high (bMSI-H) defined as sum Jensen-Shannon Distance (sumJSD) ≥0.2. Blood-based tumor mutation burden (bTMB) was defined as total SNVs and indels per Mb. Results: Of 1,301 patients, 1,148 (88%) yielded evaluable ctDNA results (COADREAD, n=487; BREAST, n=367; NSCLC, n=220; PRAD, n=74). Overall PPA with matched tissue was 90.3%. Discordant samples had significantly lower median tumor fraction by maximum somatic allele frequency (MSAF; 0.39%) than concordant samples (12.04%). Median MSAF by histology was 14% (COADREAD), 7% (BREAST), 8% (NSCLC), and 5% (PRAD). Clinically relevant fusions detected exclusively in ctDNA included RET (1% NSCLC), EML4::ALK (2% NSCLC), FGFR2 (1% COADREAD; 2% BREAST), and NTRK1 (<1% COADREAD and BREAST), corresponding to actionable NCI-MATCH arms [ FGFR2/3 - arm K (erdafitinib), ALK - arm F (crizotinib), NTRK - arm Z1E (larotrectinib)]. Actionable ctDNA-only mutations in PRAD included ATM and MLH1. Twenty-eight cases were bMSI-H (MSAF ≥0.02; sumJSD ≥0.2), of which 13 were mismatch repair-deficient by tissue testing (MLH1/MSH2 nuclear stain-negative). bMSI-H was most frequent in COADREAD (7%). Ten cases (seven COADREAD, two NSCLC, one PRAD) were MMR-proficient by tissue but bMSI-H by ctDNA. Twenty-four cases had high bTMB (≥20 mut/Mb; MSAF ≥0.02), all of which were also bMSI-H. Conclusions: ctDNA - tissue concordance NCI-MATCH in these four cancer histologies was high (90.3%), supporting liquid biopsy as a practical alternative when tissue is unavailable. Detection of ctDNA-only alterations highlights tumor heterogeneity in advanced cancers and identifies additional therapeutic opportunities.

This work deals with the effect of cooling rate on microstructure, dislocation density, and microhardness of laser direct energy deposited Inconel 718. Thermocycles were captured during direct energy deposition process using an infrared pyrometer. Cooling rate was estimated from the thermocycles at various laser powers and scanning speeds. In addition, a numerical model was developed to calculate cooling rate at different laser process parameters, and the same was verified with the experimental results. Microstructure and phases of the direct energy deposited Inconel 718 were observed using a scanning electron microscope and X-ray diffractometer, respectively. Top layer of the cladding was found to consist of fine equiaxed grains, whereas columnar dendrites were observed at the interface region of cladding layer and substrate. This is attributed to the variation in cooling rates between the top layer of the cladding and the interface region. gamma, gamma ', gamma '' and Laves phases were identified to be the primary phases in the cladding layer. Moreover, niobium content was found to be high and varying with the cooling rate in the direct energy deposited Inconel 718. Dislocation density at varying scanning speed, i.e., cooling rate was estimated using the Williamson-Hall method. An increase in the dislocation density and concomitant improvement in the hardness was found with an increase in the cooling rate.

3006 Background: During NCI-MATCH (NCT02465060) clinical trial screening, 5961 advanced cancer patients underwent next-generation sequencing to assess eligibility. About 60% of these patients had less common tumors (i.e., cancers other than colon, rectal, breast, non-small cell lung, or prostate). Most patients lacked a study eligible mutation of interest (MOI) and thus didn’t receive a trial therapy. Analysis of plasma samples from these patients may illuminate circulating tumor DNA (ctDNA) profiles, potentially guiding ctDNA testing for clinically relevant mutations in less common cancer types. Here we report the molecular profiles of ctDNA and matched tumor from a subset of the NCI-MATCH screened patients. Methods: Comprehensive genomic profiling of ctDNA (from blood collected at enrollment) was performed using the TSO500 ctDNA v2 assay (523-genes) and sequenced on the Illumina NovaSeq 6000. Matched tumor was sequenced with the Oncomine Comprehensive Assay v2, a 143-gene panel. Positive percent agreement (PPA) between mutations of interest (MOI) identified in plasma ctDNA and tissue-based screening was calculated with tumor tissue as referent (PPA ref_tumor ). Results: We tested 2253 patients from the less common tumor cohort. 2194 samples were evaluable with 98.6% pass and 1.4% failure rates. A subset of five tumor histologies with larger representation (n > 35) in sample size were further analyzed: cholangiocarcinoma (CCA, n = 90), small cell lung cancer (SCLC, n = 59), adenocarcinoma of the esophagus (EAC, n = 37), adenocarcinoma of the pancreas (PDAC, n = 232), and salivary gland cancer (SGC, n = 47). Overall, PPA ref tumor was 83.4% (range: 76.5%-97.9%) in these five histologies. In patients with concordance < 75%, median tumor fraction (as determined by maximum somatic allele frequency) was much lower (0.37%) than for specimens with concordance > = 75% (6.49%). The most frequently mutated genes identified in CCA were TP53 , KRAS , and IDH1 ; in SCLC were TP53 and RB1 loss; in EAC were TP53 , KRAS, and ERRB2 amplification; in PDAC were TP53 and KRAS ; and in SGC was TP53 . Additionally, there were several clinically relevant mutations detected only in ctDNA such as IDH1 for CCA; and BRAF , TP53 , and PIK3CA in several histologies. Microsatellite instability, as measured only in ctDNA, was most prevalent in SCLC, followed by CCA. Conclusions: Concordance of rare tumors in the NCI-MATCH trial is 83.4% in the representative histologies analyzed, which is similar to concordance of clinically relevant MOIs in common cancer studies. Liquid biopsy may be a viable screening option for matching targeted therapies in clinical trials, especially when a tumor biopsy is not practical or evaluable. The detection of some mutations in ctDNA only may suggest the presence of tumor heterogeneity in multiple lesions in patients with less common cancers.

Carcinosarcoma (CS) is a rare aggressive biphasic tumor characterized by the presence of both carcinomatous (epithelial) and sarcomatous (mesenchymal) components. It can occur in various organs, including uterus and ovaries, and often exhibits rapid progression. The biphasic nature of CS makes it challenging to treat. In this study, we characterized a patient-derived xenograft (PDX) model developed from a 27 year-old female with CS of unknown primary origin in the NCI Patient-Derived Models Repository (https://pdmr.cancer.gov) to understand the transcriptomic features of these different components. PDX samples of the tumor were iteratively passaged in separate NSG mice, and samples from different lineages across passages P0-P2 were collected for analysis. Twenty-five separate carcinoma/sarcoma regions from 7 samples through laser capture microdissection were obtained for bulk RNA-seq. Fourteen samples were sequenced through single-cell RNA-seq using 10x Genomics Single Cell Chromium, including 2 samples in P0, 8 in P1 and 4 in P2. Mouse reads were excluded using XenoCell. Human-only reads were processed through standard QC filtering, integration and annotation with Cell Ranger, Seurat and other R packages. After quality-based filtering, we obtained 24,648 single cells from the integrated tumor samples. Through unsupervised clustering, cells separated into 16 Seurat-identified clusters, with consistent percentages of carcinoma and sarcoma components in P0, P1 and P2. Based on gene expression signature scores, each cluster was given a label descriptive of the cluster status. Five clusters had more epithelial/carcinoma characteristics (including one with a distinct ciliated signature), 2 clusters displayed a clear mesenchymal/sarcoma phenotype, 4 had low reads or gene counts, 2 had high cell cycle signature score and 3 clusters did not have a distinct carcinoma or sarcoma status. We identified differentially expressed genes in each annotated cluster relative to the other clusters and performed gene set enrichment analysis. Individual carcinoma clusters demonstrated upregulation of pathways related to apoptosis, hypoxia and inflammation (p-value < 0.05), while sarcoma clusters demonstrated upregulation of WNT signaling, EMT and angiogenesis (p-value < 0.05). Clusters with unclear carcinoma/sarcoma phenotype showed patterns of expression similar to carcinoma clusters, with the additional activation of oxidative phosphorylation and DNA repair pathways. Single cell data for a CS PDX model show that the biphasic nature of this histology is stable through passaging. Using single cell data, we identified the presence of clusters that are not fully committed to either the carcinoma or sarcoma phenotype. These clusters could represent transitional cell populations which may provide insight into biological drivers of cell plasticity in this tumor histology. Alida Palmisano, Yuri Kotliarov, Parimal Kumar, Ting-Chia Chang, Li Chen, Brandie Fullmer, Alyssa Chapman, Amanda Peach, Biswajit Das, Tomas Vilimas, Thomas Forbes, Shahanawaz Jiwani, Melinda G. Hollingshead, Yvonne A. Evrard, Sarah Shin, Hari Sankaran, Julia Krushkal, Alice Chen, Yingdong Zhao, Chris A. Karlovich, Mickey Williams, Lisa M. McShane, James H. Doroshow. Single-cell characterization of a carcinosarcoma patient-derived xenograft model [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 5078.

Rare tumors are unique cancers that often present distinct biological behaviors and treatment responses. Researchers face significant challenges in the study of those tumors due to limited patient samples, lack of comprehensive genomic data, and difficulties in establishing appropriate preclinical models for effective drug testing. The identification of effective drug combinations for cancer treatment remains a major challenge, largely due to tumor heterogeneity and variable therapeutic responses. ATR is a key kinase involved in the DNA damage response. The combination of ATR inhibitors with temozolomide (TMZ) [ATRi+TMZ] enhances the cytotoxic effects of TMZ by targeting DNA damage response pathways, particularly in cancer cells with impaired DNA repair mechanisms, offering a promising therapeutic strategy for tumors resistant to conventional treatments. This study utilized gene expression profiling of 38 rare tumor patient-derived xenograft (PDX) models available in the NCI Patient-Derived Models Repository (PDMR) (https://pdmr.cancer.gov) to identify potential biomarkers that predict responses to TMZ combined with either of two ATR inhibitors, i.e., AZD6738 (Ceralasertib) and BAY1895344 (Elimusertib). We conducted comprehensive analyses including gene expression correlation with response, network interaction and gene set enrichment analysis. Our study revealed that lower MGMT expression (i.e., MGMTlow, normalized count <50) in PDX models was associated with sensitivity to ATRi+TMZ combination therapy as expected; 3/4 and 4/4 MGMTlow models were sensitive to AZD6738+TMZ and BAY1895344+TMZ combination, respectively. However, MGMThigh status did not necessarily denote resistance; a portion of MGMThigh models were also sensitive to the ATRi+TMZ combinations. In MGMThigh PDXs, network analysis and GSEA revealed that ATRi+TMZ sensitive models had significant (p<0.001) enrichment of highly expressed DNA replication genes such as MCM2 compared to resistant models. Moreover, elevated MCM2 expression was associated with sensitivity to ATRi+TMZ: 8/8 and 7/9 MGMThigh/MCM2high models were sensitive to AZD6738+TMZ and BAY1895344+TMZ, respectively. Correspondingly, 14/18 and 24/24 MGMThigh/MCM2low PDX models were resistant to AZD6738+TMZ and BAY1895344+TMZ, respectively. We used mass spectrometry-based proteomics data from a subset of rare tumor models in our RNAseq-based dataset to validate the MGMT/MCM2 expression association with ATRi+TMZ response, confirming a similar trend. Our findings revealed distinct expression signatures associated with favorable responses to two ATR inhibitors when individually combined with TMZ, highlighting candidate markers that could guide treatment decisions. Additional validation in a larger study would establish the potential utility of these candidate genes for patient selection in clinical trials. Yingdong Zhao, Mariam M. Konate, Ming-Chung Li, Peter I. Wu, Li Chen, Lindsay Dutko, Alyssa Chapman, Nikitha Nair, Melinda G. Hollingshead, Shahanawaz Jiwani, Biswajit Das, Julia Krushkal, Andrea R. Voth, Larry V. Rubinstein, Howard Stotler, Shannon Uzelac, Justine Mills, Tiffanie Chase-Miner, Suzanne D. Borgel, Cindy R. Timme, Lijun Chen, Yingwei Hu, Hui Zhang, Alice P. Chen, Chris A. Karlovich, P Mickey Williams, Yvonne A. Evrard, Lisa M. McShane, James H. Doroshow. Unveiling markers of response to ATR inhibitor and TMZ combinations in rare tumor PDXs [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 489.

PURPOSE:The National Cancer Institute Molecular Analysis for Therapy Choice (NCI-MATCH) (EAY131, ClinicalTrials.gov identifier: NCT02465060) trial pairs patients with targeted therapies on the basis of tumor genomic alterations. Subprotocol T assessed vismodegib, a hedgehog pathway inhibitor, in patients with Patched-1 (PTCH1) and Smoothened (SMO) alterations (excluding basal cell carcinoma). METHODS:Eligible patients received oral vismodegib (150 mg daily) until progression or toxicity. The primary end point was objective response rate, with secondary end points including 6-month progression-free survival (PFS), survival, and predictive biomarkers. Optional plasma for cell-free DNA analysis was collected at enrollment, on treatment, and at progression. RESULTS:From June 2016 to September 2020, 34 patients enrolled; 31 eligible patients (nine SMO, 22 PTCH1) received treatment, with 25 confirmed by the central NCI-MATCH assay (primary analysis cohort). Median age of the 31 eligible patients was 64 years, with 48.4% being women. Sixty-one percent received ≥3 previous therapies and 74% had multiple co-occurring mutations. Objective response rate was 8% (2/25 [90% CI, 1.4 to 23.1]) in the primary analysis cohort and 6.5% (2/31 [90% CI, 1.2 to 19]) overall. Partial responses occurred in soft tissue sarcoma (PTCH1) and meningioma (SMO), with response durations of 19 and 9.23 months, respectively. Six-month PFS rates were similar (24%, 23.2%), with an identical median PFS of 1.8 months and median overall survival of 7.3 months for the analyzable and primary analysis patient cohorts. Four patients (12.9%) discontinued therapy because of adverse events. Common toxicities included grade 1-2 fatigue, anorexia, weight loss, alopecia, and dysgeusia. Four on-study deaths occurred, none treatment-related. CONCLUSION:Vismodegib was well tolerated with mainly grade 1-2 toxicities, but it did not meet the primary end point. Select patients with specific SMO and PTCH1 alterations had notable responses, warranting further comprehensive molecular analyses to elucidate resistance mechanisms.

Head and neck (HN) cancers are a rare set of cancers defined by their anatomical point of origin including mouth, sinus, throat, or nose. Human papilloma virus (HPV) infection plays a pathogenic role in HN cancers resulting in distinct clinical and molecular characteristics from those that are HPV-. The National Cancer Institute’s Patient-Derived Models Repository (NCI PDMR; https://pdmr.cancer.gov) has developed a national repository of Patient-Derived Models (PDMs) comprised of patient-derived xenografts (PDXs), organoids (PDOrg), tumor cell cultures (PDCs) and cancer associated fibroblasts (CAFs). These models are clinically annotated with molecular information available in a public database for the extramural community. To date, 361 patient HN tumor specimens have been received from 351 unique patients across a range of histologies including lip/oral, pharyngeal, laryngeal, salivary and sinonasal with an overall PDX take rate of 48% (322 assessable specimens). The NCI PDMR currently has 200 public HN PDX, PDOrg, and PDC models from 124 unique patients. Thirty-three models (PDX, PDOrg, PDC) from 20 unique patients are positive for HPV16 or 18 (one double positive) as detected by PCR and one sinonasal PDOrg model is positive for HPV33 identified in NextGenSeq data. As has been reported in the clinical literature TP53 and CDKN2A mutations are found predominantly in PDX models that are HPV- (84% and 65%, respectively) but not HPV+ (0%; 0%) and PIK3CA is more commonly mutated in HPV+ PDX models (47% vs 25%). No significant difference in loss of heterozygosity is observed in the models. However, significant differences in chromosome arm copy number changes (copy gains in 7p, 11p and 12p and copy losses in 3p, 9p and 18q [P-value<0.05; Wilcoxon Rank-Sum test]) are observed in HPV- compared to HPV+ models. Gene set enrichment analysis (GSEA) suggest the E2F_TARGETS, G2M_CHECKPOINT, and DNA_REPAIR gene sets are significantly up-regulated in HPV+ while the APOPTOSIS gene set is significantly down-regulated using MSigDB Hallmark dataset (P-value<0.05). In all analyses, differences are consistent whether examining in vivo PDX models or in vitro PDC/PDOrg models indicating the fidelity of the models. These preclinical models recapitulate the molecular differences reported in HPV+ versus HPV- clinical cases providing an important tool for the development of novel therapeutics for HN cancers. Funded by NCI Contract No. HHSN261200800001E Yvonne A. Evrard, Ting-Chia Chang, Jasmine B'Lanton, Gareth Bliss, Alice Chen, Li Chen, Kevin Cooper, Kristin Cox, Natalie Czarra, Isabella Czernia, Biswajit Das, Kelly Dougherty, Aarin Dreyer, Lindsay Dutko, Katie Frey, Marion Gibson, Tara Grinnage-Pulley, Shahanawaz Jiwani, Poorva Juneja, Keegan Kalmbach, Tamikia Lamb, Eva Loewenstein, Candace Mallow, Chelsea McGlynn, Justine Mills, Michael Mullendore, Matthew Murphy, Sandra Navas-Reyes, Michelle Norris, Jessica Park, Kaci Paulus, Kevin Plater, Tia Shearer, Jessica Steed, Luke H. Stockwin, Howard Stotler, Ruth Thornton, Cindy R. Timme, Shannon Uzelac, Dianne L. Newton, Chris A. Karlovich, P Mickey. Williams, Melinda G. Hollingshead, James H. Doroshow. HPV+ and HPV- Head and Neck Cancer Patient-derived Models in the NCI Patient-Derived Models Repository [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference on Molecular Targets and Cancer Therapeutics; 2025 Oct 22-26; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2025;24(10 Suppl):Abstract nr C068.

PurposeThe National Cancer Institute’s Molecular Profiling-Based Assignment of Cancer Therapy (NCI-MPACT) randomized phase 2 clinical trial assessed the utility of applying tumor DNA sequencing to treatment selection. Here, we report the results of a companion preclinical study in patient-derived xenograft (PDX) models to evaluate how each tumor responded to each of the treatment regimens studied in the NCI-MPACT trial instead of simply to the specific regimen targeting the study-actionable mutation of interest (aMOI).MethodsFifty-one PDX models (46 with and 5 without NCI-MPACT aMOIs) were tested against both the arm that would have been assigned in the NCI-MPACT trial as well as every other study regimen: (1) veliparib plus temozolomide or (2) adavosertib plus carboplatin (targeting the DNA repair pathway); (3) everolimus (targeting the PI3K pathway); and (4) trametinib (targeting the RAS/RAF/MEK pathway). Durability of response was measured by relative median time to tumor quadrupling event-free survival (EFSx4 ≥ 2), and duration of tumor regression.ResultsEleven of 50 models (22%) treated with veliparib plus temozolomide responded according to one or both metrics, as did 2/47 models (4.2%) treated with adavosertib plus carboplatin, and 2/46 models (4.3%) treated with trametinib; no models responded to erlotinib. Follow-up studies demonstrated that temozolomide drove the activity of the veliparib plus temozolomide combination and drug sensitivity to temozolomide correlated with MGMT deficiency.ConclusionThis prospective preclinical study confirmed the modest response rates in the NCI-MPACT clinical trial. Substantial responses to temozolomide suggest that this drug represents an effective treatment for patients with MGMT deficiency, regardless of cancer type.

Deficiency in MGMT expression, through low gene/protein expression and/or silencing of the MGMT promoter along with a functional DNA mismatch repair pathway, significantly increases a cancer cell’s sensitivity to temozolomide (TMZ) treatment, particularly in glioblastoma. To understand whether MGMT deficiency affects response to TMZ in other cancer types, preclinical drug studies were performed in patient-derived xenograft (PDX) models selected from the NCI Patient-Derived Models Repository (PDMR: https://pdmr.cancer.gov). MGMT deficiency was measured using a CLIA-validated promoter methylation assay (PMR assay), protein expression by immunohistochemistry (IHC), and gene expression by RNAseq. Here we evaluated the concordance of MGMT status across different assays and their correlations with response to TMZ. Eighty-eight pan-cancer PDX models, including solid tumors and sarcomas, were used in TMZ preclinical studies. MGMT deficiency was determined using the following criteria: promoter methylation ratio ≥ 2 by PMR assay, low protein expression (tumor nuclear staining < 30%) by IHC, or low gene expression (z-score of normalized count < -1.65) by RNAseq. For each model, PDX samples from 2 passages were evaluated to assess consistency in MGMT promoter methylation and protein expression during passaging. The survival metric of relative median delay in tumor quadrupling for event-free survival (EFSx4) was used to quantify tumor growth delay of the models treated with TMZ. Out of 88 models, 7 models were identified as MGMT deficient and 71 models as MGMT proficient across all three assays, resulting in an assay concordance rate of 88.64% (78/88). Among the 10 discordant models, 3 were MGMT promoter unmethylated, but showed low MGMT protein and gene expression. Conversely, 5 models were MGMT promoter methylated, but had high MGMT gene and protein expression. Possible reasons for these discrepancies include differences in sensitivity of the assays and post-transcriptional/translational regulation of MGMT gene/protein expression. One urothelial/bladder cancer model showed inconsistent IHC results and one Hurthle cell neoplasm showed inconsistent PMR results between 2 passages suggesting tumor heterogeneity within these models. Comparing the EFSx4 response metric and MGMT status, MGMT-deficient models treated with TMZ had a mean EFSx4 of 1.9, 1.8, and 2.1 when detected by PMR assay (n=13), IHC (n=10), and RNAseq (n=11), respectively. These durations were statistically significant (p<0.0001, Wilcoxon rank sum test) compared with MGMT proficient models treated with TMZ (mean EFSx4 = 1.1). Three MGMT assays showed good concordance in TMZ preclinical studies using PDMR models. Substantial responses to TMZ suggest that this drug represents an effective treatment for patients with MGMT deficiency, regardless of cancer type. Li Chen, Shahanawaz Jiwani, Lindsay Dutko, Vishnu Rahul Kannan, Maria Saeed, Alyssa Chapman, Lisa Brown, Nikitha Nair, Corinne Camalier, Biswajit Das, Ting-Chia Chang, Chelsea McGlynn, Howard Stotler, Shannon Uzelac, Justine Mills, Tiffanie Chase-Miner, Cindy Timme, Yvonne Evrard, Laura Kuhlmann, Dianne Newton, Melinda Hollingshead, Chris Karlovich, Mickey Williams, James Doroshow. MGMT as a pan-cancer biomarker in temozolomide preclinical studies using models from the NCI PDMR [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference on Molecular Targets and Cancer Therapeutics; 2025 Oct 22-26; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2025;24(10 Suppl):Abstract nr A005.

BackgroundNeomorphic isocitrate dehydrogenase (IDH) mutations lead to the accumulation of 2-hydroxyglutarate (2-HG), an oncometabolite implicated in tumor progression via inhibitory effects on alpha-ketoglutarate. Moreover, mutant IDH-dependent accumulation of 2-HG results in homologous recombination deficiency (HRD), which preclinically renders tumors sensitive to poly(adenosine diphosphate ribose) polymerase inhibitors. Here, the results of the cholangiocarcinoma (CCA) arm of the National Cancer Institute (NCI) 10129 olaparib in IDH-mutant solid tumors basket trial are reported.MethodsOlaparib 300 mg twice daily was evaluated in an open-label, phase 2 clinical trial for treatment-refractory IDH-mutant solid tumors. Patients in the IDH-mutant CCA arm enrolled in two cohorts: (1) IDH inhibitor (IDHi) pretreated and (2) IDHi untreated, with a primary end point of overall response rate.ResultsNCI 10129 enrolled 30 patients with IDH-mutant CCA with no objective responses seen, and recruitment was closed early. Median progression-free survival (PFS) was 2.4 months (95% CI, 1.9 to 6.5 months) and median overall survival was 12.9 months (95% CI, 6.3 months to not reached). Eight patients (27%) had clinical benefit (CB), with a PFS of >= 6 months. Patients with CB had lower baseline 2-HG levels compared to those without CB (1.4 vs. 5.9 mu mol/L; p = .01).ConclusionsOlaparib does not have sufficient single-agent activity to warrant further development in IDH-mutant CCA. However, a subgroup of patients demonstrated CB, and exploratory analysis revealed this subgroup to be enriched for lower baseline 2-HG levels. Future clinical trials leveraging the HRD properties of IDH mutations are warranted with enhanced patient selection and novel combination therapies.

Patient-derived xenografts (PDX) have proven invaluable research and pre-clinical tools for studying cancer. NCI has been building an extensive patient-derived model repository (PDMR) of diverse histologies, many of which have been utilized for pre-clinical drug studies. In this study, we have used gene expression profiles from RNA-Seq and mutation data from whole exome sequencing (WES) to identify the molecular subtypes of PDX models from 4 major cancer types: breast, ovarian, colon, and cholangiocarcinoma. We also report the key differentially expressed genes and pathways and highlight the key mutations associated with each subtype. Gene expression data from originator patient and PDX specimens were obtained using R tximport and DESeq2 packages based on RNA-Seq data. ComBat-Seq was used to computationally alleviate batch effects between originators and PDX samples. The gene expression values were log2-transformed when being visualized via heatmap. The R genefu package was used for PAM50 classification of breast cancer models. For ovarian cancer and cholangiocarcinoma subtyping, the PAM algorithm was used on TCGA data to train the classification model. The R CMScaller package was used to predict colon cancer subtypes. We characterized the molecular subtypes of 256 PDX models from breast (n=58), ovarian (n=11), colon (n=174), and cholangiocarcinoma (n=13) tumor histologies. First, we used Least Absolute Shrinkage and Selection Operator (LASSO) to build a histology classifier and identified differential expression from many histology-specific genes such as GATA3 for breast cancer and SOX17 for ovarian cancer. This confirmed that our PDX models resemble the original patient specimens. Second, by using either a pre-trained molecular subtype classifier or a newly trained model from TCGA data, we were able to assign many molecular subtypes of clinical relevance and rediscover the gene and pathway-level molecular signatures associated with prognosis and treatment response. Finally, we observed the expected mutation profiles for the identified subtypes in the WES data, such as a significant increase for the TP53 mutations and decrease of PIK3CA mutations in Basal subtypes compared to other breast cancer subtypes. The NCI PDMR provides an extensive resource for preclinical studies of molecular subtypes of cancer, as demonstrated by our ability to carry out subtype-specific analysis based on gene expression and mutational profiles. We were able to characterize, for example, the basal subtype of breast cancer and the mesenchymal subtype of colon cancer, both of which remain among the most challenging subtypes to treat. The presented molecular subtypes here could not only guide the future direction for translational projects, but also serve as a reference point for other high-impact research topics. I-Fan Wu, Li Chen, Shahanawaz Jiwani, Cindy R. Timme, Yvonne A. Evrard, Biswajit Das, Kelly Benauer, Gonzalo Salguero. Corado, Ruth Thornton, Irene Song, Poorva Juneja, Thomas Forbes, Dianne Newton, Melinda G. Hollingshead, Chris A. Karlovich, James H. Doroshow. Molecular subtyping of NCI PDMR models using gene expression profiles [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference on Molecular Targets and Cancer Therapeutics; 2025 Oct 22-26; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2025;24(10 Suppl):Abstract nr C066.

Abstract Background: Patient-derived xenograft (PDX) models serve as a powerful tool for cancer translational research. However, it is unclear to what extent PDX models reflect the genomic intratumoral heterogeneity and genomic aberrations present within the original tumor sample. The National Cancer Institute (NCI) has developed a Patient-Derived Models Repository (PDMR; https://pdmr.cancer.gov/) consisting of PDX, organoids (PDOrg), and tumor cell cultures (PDC) from patients with diverse cancer histologies. We have conducted an in-depth investigation into the genomic stability of PDXs at early passaging and tumor heterogeneity in a large set of preclinical models including rare cancers. Methods: Tumor specimens were used to establish 1114 models from 1034 patients. For whole exome sequencing (WES) and RNASeq analysis, 1059 models with at least 1 PDX sample and 55 models with only a PDC or PDOrg were used. Analyzed specimens represent the original patient specimens, PDX passages P0, P1, P2, and P3+ and in vitro models. 80% of the PDX specimens were within passages P0 to P2. Results: Genomic stability in PDMR models was maintained through early passages (P0 - P2) and across independent lineages in PDMR models based on the following observations: 1) variant allele frequencies (VAF) of somatic driver mutations showed no major deviations (exceeding ±10%) when using the stromal fraction corrected VAF from originator data over PDX passages; 2) the median change in the fraction of genome impacted by copy number alterations (CNA) from the originator specimens through passages P0 - P2 was statistically inconsequential, although there was a significant increase in CNA fraction, from 5.3% at P0 initially to 18% by P3; 3) gene expression profiles of specimens within a given PDX model formed clusters in principal component analysis (PCA) plots and showed high correlation (>99.5% models with a Spearman coefficient of >= 0.8). The majority of the PDC and PDOrg specimens exhibited similar findings when compared to the original tumor samples. Furthermore, the positive percent agreement (PPA) was performed to measure the similarity between the patient's tumor and all available derived PDX specimens, with a median PPA over 90%, indicating a high level of retained heterogeneity within the PDX models. Lastly, 69% of models in NCI PDMR had predictive biomarkers, ranging from OncoKB level of evidence 1-4, which could be used to evaluate targeted therapeutics in preclinical studies. Conclusion: The NCI PDMR has a large and histologically diverse cancer representation. In this analysis, the PDXs exhibited genomic stability within early passages and preserved the majority of tumor heterogeneity observed in the patient specimens. NCI PDMR thus represents a valuable resource for researchers interested in preclinical drug screening or other investigations. Citation Format: Ting-Chia Chang, Biswajit Das, Li Chen, Peter I-Fan Wu, Yvonne A. Evrard, Rini Pauly, Dianne L. Newton, Shahanawaz Jiwani, Sergio Y. Alcoser, Luke H. Stockwin, Corinne E. Camalier, Tomas Forbes, Nikitha Nair, Alyssa Chapman, Lindsay Dutko, Michael Mullendore, Tara Grinnage-Pulley, Kimberly Klarmann, Sarah B. Miller, Chris A. Karlovich, Alice P. Chen, P Mickey Williams, Melinda G. Hollingshead, James H. Doroshow. Genomic landscape and stability of preclinical models in NCI's patient-derived models repository [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6914.

5579 Background: During the screening phase of the National Cancer Institute Molecular Analysis for Therapy Choice (NCI-MATCH; NCT02465060) trial, 5954 patients with advanced cancer, approximately 60% of whom had rare or less common cancers, underwent next-generation sequencing of their tumor tissue to determine study eligibility. The majority of the patients could not be assigned to a treatment arm because they did not have a study mutation of interest (MOI). The plasma collected from these patients may provide insight into the genomic landscape of circulating tumor DNA (ctDNA) and inform the potential utility of ctDNA testing for the identification of clinically relevant mutations in these rare histologies. Here we report the molecular profiles of ctDNA from a subset of the NCI-MATCH screened patients with gynecologic cancers. Methods: Cell-free DNA (cfDNA) was extracted and quantitated from plasma collected in Streck blood tubes at study enrollment. Libraries were constructed using the NCI ctDNA v2 assay with a minimum input of 10 ng and were sequenced on the Illumina NovaSeq 6000 with S4 flow cells. Results: Among 200 samples sequenced, four different histologies were represented: uterine endometrioid adenocarcinoma (UEC, n=51), serous endometrial adenocarcinoma (USC, n=35), uterine leiomyosarcoma (ULMS, n=40), and ovarian epithelial (OVT, n=74). Two samples failed, one ULMS due to sequencing error and one OVT due to contamination. The positive percent agreement (PPA) values calculated from clinically relevant MOI derived from OncoKb as both PPAref_tumor and PPAref_ctDNA, were 88.6% and 44.1% respectively. The most commonly mutated genes were TP53, KRAS, CTNNB1, and PIK3CA. Additionally, the ctDNA detected mutations not identified in the tumor, including 8 patients (4%) with a PIK3CA mutation. By employing predefined cutoffs of tumor fractions, ctDNA identified 21 out of 25 expected copy number amplifications demonstrating an 84% concordance. Microsatellite instability (MSI) using ctDNA was highest in the UEC (17.6% of patients) followed by USC at 8.6%, OVT at 6.8%, and ULMS at 2.6%. Among the patients with mismatch repair deficiency (MMRd) identified by tumor immunohistochemistry, 50% were identified as MSI-High in plasma. Conclusions: In this cohort of patients with advanced gynecological cancers from the NCI-MATCH trial, clinically relevant mutations detected by ctDNA were 88.6% concordant with data derived from tumor biopsy. In addition, some mutations were identified only in ctDNA, which may be due to tumor heterogenity. The data suggest that liquid biopsy is valuable as a complement to tumor biopsy data and when tissue is unavailable.

Abstract Background: Studying protein expression involved in cancer from patient-derived xenografts (PDX) enhances understanding of tumorigenesis and may shed light on patient therapeutic decisions. Recently, mass spectrometry-based proteomics sequencing techniques have enabled the acquisition of high-throughput PDX protein/phosphoprotein expression profiles and paved a way for investigating oncogenic signaling pathways and their interactions in different tumor histologies. Integrated analysis of these proteomic data with existing biomarkers derived from whole exome and RNAseq data will provide the community with a rich resource for translational research. Materials and methods: iTRAQ-based proteomics/phospho-proteomics data, with 11 Tandem Mass Tag (TMT) channels, were processed and median-normalized at gene level. The gene expression data were derived from tximport and DESeq2 from of RNA-Seq. In addition, whole exome sequencing (WES) data were used to compute mutations and copy number profiles. For data visualization, the R Bioconductor package ComplexHeatmap was used extensively. Results: PDX proteomics/phospho-proteomics data were analyzed alongside with gene expression, copy number and mutational profiles for several cancer types, revealing vivid molecular regulation for many cancer-related pathways. A moderate yet significant Spearman correlation coefficient of over 0.45 and 0.5 was observed between proteomics and RNA-Seq data at gene and pathway level, respectively. The PDX protein and gene expression pattern from common cancer regulatory pathways of bladder (BLCA, n=32 models), colon (COAD, n=82), lung (NSCLC, n=32), pancreatic (PAAD, n=52), metastatic breast cancer (CSNOS) (n=16) and other histologies were aggregated and discussed at the model level. EGFR, MET and cell-cycle genes CDKN2A and CDKN2B exhibited significant positive correlation among copy number, gene expression and protein expression profiles. Protein and gene expression profiles of PAM50 genes were shown for CSNOS samples, to further sub-classify or correct misclassification. Further analysis using proteomics/phospho-proteomics data with CNA identified several trans-regulatory events. Lastly, we identified RTN1 as a potential biomarker, exhibiting lower expression in sensitive rare-tumor PDX models prior to Axitinib and Vandetanib treatment. Conclusions: With the multi-omics datasets comprising proteomics/phospho-proteomics, RNA-Seq and WES datasets from the NCI Patient Derived Models Repository cohort, we were able to query some important cancer biological processes at a higher resolution. In addition, we revealed gene- and pathway-level regulatory differences from various histologies. Overall, the multi-omics data from PDX models showed promising recapitulation of original tumor activity and should continue to serve as an amenable and scalable drug screening platform for pre-clinical trials. Citation Format: Peter I. Wu, Li Chen, Yuri Kotliarov, Jianwen Fang, Yingdong Zhao, Yvonne Evrard, Lijun Chen, Shahanawaz Jiwani, Biswajit Das, Chris A. Karlovich, Hui Zhang, Lisa McShane, Melinda G. Hollingshead, Mickey Williams, James H. Doroshow. Integrated proteogenomic analysis for the NCI patient-derived cancer model repository [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6915.

11526 Background: There are no FDA-approved treatments for advanced cCS. Chemotherapy provides limited benefit. IDH1/2 mutations (m) occur in 50% of cCS. Both IDHm and wild-type cCS harbor epigenetic dysregulation. In preclinical models, HDAC + DNMT inhibition (i) suppressed growth by inducing apoptosis, reversing the hypermethylated state, and upregulating expression of interferon (IFN) response genes including PDL1(1). This prompted a phase 2 study of HDACi + DNMTi in cCS, which failed to meet the 1° endpoint of ORR. The majority of pts had a best response of stable disease, with a trend towards improved mPFS in IDHm (2). Here we report correlative analysis of NCI 10330. Methods: NCI 10330 is a single-arm, multicenter, phase 2 study of belinostat with SGI-110 or ASTX727 in advanced cCS. All pts were required to have pre- and on-treatment (tx) biopsies (Cycle 2, Day 3-5). Tissue was evaluated with whole exome sequencing (WES) and RNA sequencing (RNAseq). From RNAseq, Tumor Inflammation Signature Scores (TISS) and Tumor Microenvironment functional Gene Set Enrichment Analysis scores (TME GSEA) were calculated as the mean of the log2 normalized counts of 18 signature genes (Danaher et al. J Imm Can 2018) and pre-defined gene sets (3), respectively. Wilcoxon rank sum test was used to analyze TME GSEA between pre- and on-tx samples. Differential expression was significant if |FC| > 1.33, adjusted P <0.01. Results: 19 pts were treated; all received paired biopsies. WES was adequate in 7/19 (37%) pts, with IDHm identified in 3/7 (43%) pts. All pts were MSI-stable, TMB: 1.01-3.57 mut/Mb. RNAseq was adequate in 7/19 (37%) pts at pre-tx and 5/19 (26%) pts at on-tx. TISS ranges trended higher for pre-tx (8.77-10.14) vs on-tx (7.36-9.51) samples. TME GSEA identified significantly enriched tumor immune infiltration (p < 0.05) in pre- vs on-tx samples. Differential analysis identified several gene sets related to inflammation overexpressed in pre-tx samples only, including IFN response. On-tx samples were enriched in myogenesis and coagulation gene sets. Conclusions: This is the first study to describe transcriptomic changes following epigenetic tx in cCS. Contradictory to our preclinical data, HDACi + DNTMi resulted in low expression of inflammation. Prior studies reported that the immune infiltrate of CS at progression is immunosuppressive; higher immune infiltrate is correlated with worse outcomes (4). Loss of inflammation may have implications for disease stability experienced by most pts on NCI 10330. Further analyses are planned to correlate TME (pro- vs anti-inflammatory infiltrates) and outcomes. Analyses are limited by small sample size, highlighting the challenges in collecting adequate CS specimens. 1. Sheikh, Schwartz et al. Mol Cancer Ther 2021. 2. Lacuna et al. ASCO 2023: #11531. 3. Bagaev et al. Can Cell 2021. 4. Richert et al. J Bone Onc 2020. Clinical trial information: NCT04340843 .

Abstract Cholangiocarcinoma (CHOL) is an aggressive rare malignancy arising in the biliary tract with a 5-year relative survival rate of 10% and a 60-70% recurrence rate following surgical intervention. Advances in treatment strategies are hampered by the lack of well annotated and characterized preclinical models. The National Cancer Institute’s Patient-Derived Models Repository (NCI PDMR; https://pdmr.cancer.gov) has developed a national repository of Patient-Derived Models (PDMs) comprised of patient-derived xenografts (PDXs), in vitro patient-derived tumor cell cultures (PDCs) and cancer associated fibroblasts (CAFs) as well as patient-derived organoids (PDOrg). These PDMs are clinically annotated with molecular information available in an easily accessible database for the extramural community. To date, 94 patient CHOL tumor specimens (resections, biopsies, rapid autopsy) have been received from 55 unique patients with an overall PDX take rate of 36.3% (80 assessable specimens). There are currently 15 CHOL PDX models available for the research community to request with 14 more in final QC. Nine of the 15 public PDX models were generated from unique lesions in two rapid autopsy patients and while histo-morphologically consistent, some genomic heterogeneity is observed between the unique anatomical locations likely due to tumor evolution during metastasis. In addition, 27 in vitro PDOrgs, PDCs, and CAFs have been generated from patient or PDX material matched to most of the existing PDX models to allow for comparative translation research. The genetic landscape of the CHOL PDXs includes oncogenic drivers in NRAS, IDH1, ERBB2, TP53, KRAS and FGFR2 fusions; OncoKB likely oncogenic variants including ARID1A, AXIN1 and BAP1; and CDKN2A deep deletions representing most of the common alterations in CHOL. Early passage preclinical PDX and in vitro models for CHOL, and many other cancer types, with translational relevant features along with associated NextGen sequencing and patient treatment history are available from the NCI PDMR. Availability of preclinical models that can be used to study these cancers and improve preclinical drug screening is of high importance to better understand the biology of these cancers and prioritize novel therapeutics from bench to clinic. Funded by NCI Contract No. HHSN261200800001E Citation Format: Yvonne A. Evrard, Cindy R. Timme, Biswajit Das, Gareth Bliss, Carrie Bonomi, Carley Border, Ting-Chia Chang, Alice Chen, Li Chen, Michelle A. Crespo-Eugeni, Kevin Cooper, Natalie Czarra, Isabella Czernia, Kelly Dougherty, Marion Gibson, Tara Grinnage-Pulley, Shahanawaz Jiwani, Keegan Kalmbach, Chris A. Karlovich, Chelsea McGlynn, Michael Mullendore, Matthew Murphy, Rini Pauly, Kevin Plater, Jessica Steed, Luke Stockwin, Shannon Uzelac, Peter I-Fan Wu, Dianne L. Newton, P. Mickey Williams, Melinda G. Hollingshead, James H. Doroshow. Cholangiocarcinoma patient-derived models in the NCI Patient-Derived Models Repository [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6898.