Differential Drug Response Research Articles

Engineered Age-Mimetic Breast Cancer Models Reveal Differential Drug Responses in Young and Aged Microenvironments.

Aging is one of the most significant risk factors for breast cancer. With the growing interests in the alterations of the aging breast tissue microenvironment, it has been identified that aging is related to tumorigenesis, invasion, and drug resistance. However, current pre-clinical disease models often neglect the impact of aging and sometimes result in worse clinical outcomes. In this study, we utilized aged animal-generated materials to create and validate a novel age-mimetic breast cancer model that generates an aging microenvironment for cells and alters cells towards a phenotype found in the aged environment. Furthermore, we utilized the age-mimetic models for 3D breast cancer invasion assessment and high-throughput screening of over 700 drugs in the FDA-approved drug library. We identified 36 potential effective drug targets and 34 potential drug targets with different drug responses in different age groups, demonstrating the potential of this age-mimetic breast cancer model for further in-depth breast cancer studies and drug development.

Novel Intraprostatic MR-Guided Implantation of Multidrug-Eluting Microdevice for Testing of Systemic Therapy Agents In Situ: Proof of Concept in Intermediate-Risk and High-Risk Prostate Cancer.

The purpose of this study was to assess safety and feasibility of percutaneous MR-guided placement of an implantable microdevice (IMD) to evaluate in situ intratumor response to multiple pharmacologic agents in men with intermediate-risk and high-risk localized prostate cancer. Biocompatible IMDs measuring 750 µm in diameter and 5 mm in length were prepared with 20 reservoirs containing candidate drug and drug combinations including second-generation androgen inhibitors, PARP inhibitors, PD-1 inhibitors, and conventional chemotherapy. Men with intermediate-risk or high-risk localized prostate cancer and MRI-visible lesions were enrolled. Up to 4 IMDs were placed using a transperineal approach into MRI-visible tumors 2 days before planned radical prostatectomy. After radical prostatectomy, the IMDs and a small segment of surrounding tumor tissue were removed and sectioned, stained, and analyzed for tissue drug response by a variety of pharmacodynamic markers. Fourteen patients were enrolled: 7 (50%) with intermediate-risk and 7 (50%) with high-risk localized prostate cancer. A total of 53 IMDs were implanted (mean 3.8 per patient), and 49 IMDs (92%) were successfully retrieved. All men underwent uncomplicated robotic-assisted radical prostatectomy and bilateral pelvic lymph node dissection 2 days after IMD placement. There were no severe adverse events. Pathological examination of the tissues adjacent to the IMDs demonstrated differential drug response within patients and between patients. Limitations include small sample size. A multidrug IMD can be safely placed percutaneously into MRI-visible lesions before radical prostatectomy, enabling assessment of tumor-specific local response to multiple agents simultaneously within the tumor's normal stromal environment to guide targeted systemic therapy.

Beyond One-Size-Fits-All: Personalized Medicine and Future Directions in Sex-Based Psychopharmacological Treatment

Sex-related differences in psychopharmacology present unique challenges in both clinical and research settings. Recognition of sex differences in psychopharmacological treatment has increased in recent years, but a significant research gap regarding variations between men and women still exists. Biological factors, including hormonal fluctuations, genetic factors, and brain structure differences, contribute significantly to differential drug responses. Moreover, social determinants can influence the differential burden of psychiatric disorders between the sexes and may impact treatment plans. Incorporating sex as a key variable in personalized treatment programs and plans holds the potential to optimize efficacy and minimize adverse effects in psychopharmacology. Sex-related challenges in psychopharmacology necessitate a nuanced approach to treatment. Further research is needed to fully understand these differences and to develop guidelines for personalized medication management. By addressing these challenges, clinicians can improve treatment outcomes and enhance the quality of life of patients with psychiatric disorders.

Using electronic health records for clinical pharmacology research: Challenges and considerations.

Electronic health records (EHRs) contain a vast array of phenotypic data on large numbers of individuals, often collected over decades. Due to the wealth of information, EHR data have emerged as a powerful resource to make first discoveries and identify disparities in our healthcare system. While the number of EHR-based studies has exploded in recent years, most of these studies are directed at associations with disease rather than pharmacotherapeutic outcomes, such as drug response or adverse drug reactions. This is largely due to challenges specific to deriving drug-related phenotypes from the EHR. There is great potential for EHR-based discovery in clinical pharmacology research, and there is a critical need to address specific challenges related to accurate and reproducible derivation of drug-related phenotypes from the EHR. This review provides a detailed evaluation of challenges and considerations for deriving drug-related data from EHRs. We provide an examination of EHR-based computable phenotypes and discuss cutting-edge approaches to map medication information for clinical pharmacology research, including medication-based computable phenotypes and natural language processing. We also discuss additional considerations such as data structure, heterogeneity and missing data, rare phenotypes, and diversity within the EHR. By further understanding the complexities associated with conducting clinical pharmacology research using EHR-based data, investigators will be better equipped to design thoughtful studies with more reproducible results. Progress in utilizing EHRs for clinical pharmacology research should lead to significant advances in our ability to understand differential drug response and predict adverse drug reactions.

HGG-29. INTEGRATED MOLECULAR PROFILING OF >2000 PAEDIATRIC-TYPE DIFFUSE HIGH-GRADE GLIOMA TUMOURS AND >100 PATIENT-DERIVED MODELS

Abstract BACKGROUND Paediatric-type diffuse high-grade glioma (PDHGG) is recognised in the WHO2021 CNS Tumour Classification as biologically distinct from ‘adult-types’, and comprises four major categories based on distinct biology and clinical presentation, though sub-types within these are less well-defined. METHODS Published and unpublished genome/exome/targeted sequencing from n=1593 cases were integrated with n=2027 cases with methylation array profiling, with an overlap of n=761. These were supplemented with varying availability of bulk/single-cell RNAseq, ChIP-seq and ATAC-seq, and analysed alongside data from ~100 patient-derived models representing 16 PDHGG sub-types. RESULTS Around half of cases were diffuse midline glioma with H3K27 alterations (DMG-H3K27), which can be split into sub-types based upon either the specific histone alteration (DMG-H3.3K27M/-H3.1K27M/-EZHIP) or co-segregating pathway activating mutations (DMG-EGFR/-MAPK/-ACVR1). These showed distinct copy number, transcriptomic and epigenetic signatures depending on the anatomical location, replicated in ~50 models established as 2D/3D cultures and CDX/PDX. By contrast, diffuse hemispheric glioma with H3G34 mutations (DHG-H3G34) presented a homogenous genomic landscape (TP53/ATRX/PDGFRA) but with a higher degree of transcriptional diversity in both tumours and models. In high-grade glioma, H3/IDH-wild-type (HGG-WT) samples, receptor tyrosine kinase (RTK) subtypes are split by the presence or absence of co-segregating mutations (BCOR/SETD2/NF1) and copy number changes. Across methylation-based subtypes, genetic drivers are associated with distinct phenotypes or drug responses independent of location. EGFR mutations are largely confined to the highly infiltrative pedHGG_RTK2 hemispheric (enriched in gliomatosis cerebri) and DMG-EGFR (bithalamic glioma) subtypes, whilst PDGFRAmutations span DMG-H3.3K27M, DHG-H3G34, and pedHGG-RTK1, and exhibit a differential drug response to targeted therapies depending on the nature of the alteration. Hypermutant tumours are split between pedHGG-RTK1A and the emerging ‘HGG-E’ subtype. CONCLUSIONS These data aim to catalogue the diversity of PDHGG subtypes in order to identify biologically rational targets, and credential patient-derived models which can be exploited for mechanistic/preclinical studies.

Sex affects transcriptional associations with schizophrenia across the dorsolateral prefrontal cortex, hippocampus, and caudate nucleus

Schizophrenia is a complex neuropsychiatric disorder with sexually dimorphic features, including differential symptomatology, drug responsiveness, and male incidence rate. Prior large-scale transcriptome analyses for sex differences in schizophrenia have focused on the prefrontal cortex. Analyzing BrainSeq Consortium data (caudate nucleus: n = 399, dorsolateral prefrontal cortex: n = 377, and hippocampus: n = 394), we identified 831 unique genes that exhibit sex differences across brain regions, enriched for immune-related pathways. We observed X-chromosome dosage reduction in the hippocampus of male individuals with schizophrenia. Our sex interaction model revealed 148 junctions dysregulated in a sex-specific manner in schizophrenia. Sex-specific schizophrenia analysis identified dozens of differentially expressed genes, notably enriched in immune-related pathways. Finally, our sex-interacting expression quantitative trait loci analysis revealed 704 unique genes, nine associated with schizophrenia risk. These findings emphasize the importance of sex-informed analysis of sexually dimorphic traits, inform personalized therapeutic strategies in schizophrenia, and highlight the need for increased female samples for schizophrenia analyses.

Identification of SUMOylation-related biomarkers in papillary thyroid carcinoma

BackgroundSmall ubiquitin-like modifier (SUMO) modification is increasingly recognized as critical in tumorigenesis and progression. This study identifies biomarkers linked to SUMOylation in papillary thyroid carcinoma (PTC), aiming to advance therapeutic and prognostic strategies.MethodsEmploying PTC datasets and SUMO related genes (SRGs), we utilized univariate Cox regression for prognosis-related SRGs, conducted differential expression analyses, and integrated findings to pinpoint candidate genes. These genes underwent further validation through survival, gene set enrichment, immune infiltration, and drug sensitivity analyses, including external validation via quantitative RT-qPCR. In our final step, we conducted immunohistochemical staining on tumor samples from PTC patients at our center and integrated this with their clinical data to validate BMP8A’s effectiveness in predicting recurrence in PTC.ResultsThree biomarkers—BMP8A, RGS8, and SERPIND1—emerged as significant. Gene Set Enrichment Analysis (GSEA) showed their involvement in immune-related pathways, with differential immune infiltration patterns and drug response correlations observed, underscoring their potential for targeted therapy. Lastly, we validated the efficacy of BMP8A in predicting the recurrence of PTC in patients using clinical and pathological data from our center.ConclusionThe study identifies BMP8A, RGS8, and SERPIND1 as key biomarkers associated with SUMOylation in PTC. Their linkage to immune response and drug sensitivity highlights their importance as targets for therapeutic intervention and prognosis in PTC research.

Abstract 297: Role of purine metabolism in CLL cell pathobiology and CLL disease progression

Abstract The treatment of Chronic lymphocytic leukemia (CLL) has been revolutionized in recent years, however CLL is still incurable, and the leukemic cells often develop drug resistance. Previous studies show that the interaction of CLL cells with the bone marrow (BM) microenvironment promotes spontaneous and drug induced survival. But the nature of this interaction is still in need of a full understanding. To pursue this we discerned RNA profiles using RNA-seq in paired CLL cells isolated from untreated blood and BM (n=6) and in untreated patients CLL cells (n=4) cultured alone or cocultured with BM stromal cells (BMSCs). CLL cells from blood/BM and CLL cells cultured alone or with BMSCs were examined by Western blot (WB), untargeted metabolomics (LCMS+GCMS) and preclinical drug sensitivity assays. We found upregulation of 232 genes in CLL cells from BM vs the paired blood and 917 genes in cocultured CLL cells compared to CLL cells cultured alone (p&lt0.05, fold change &gt1.5). Here we detected only 13 genes that overlap between BM and cocultured CLL cells. When we analyzed the expression of these 13 genes in blood CLL cells from a cohort of 162 untreated patients by RNA-seq we found a positive relationship between 4 (PNP, C16orf54, MOB3A, CDK2AP2) with CLL patient clinical outcome including overall survival (OS), progression free survival (PFS), and time to first treatment (TTFT) [multivariable Cox proportional hazards models, p&lt0.05]. Out of the 4 genes, purine nucleoside phosphorylase (PNP), an enzyme in the purine salvage pathway, showed the most significant association for patient’s OS, PFS, and TTFT. Metabolomic profiling indicated an increased level of purine salvage pathway metabolites adenosine, inosine, and hypoxanthine in cocultured CLL cells. WB analysis using blood CLL cells from untreated patients showed a variable PNP protein expression (high, low/no PNP) and induction in PNP protein levels were found in blood CLL cells expressing low/no PNP only when in contact with BM/BMSCs. But PNP inhibitor forodesine did not show any significant killing in high vs low/no PNP group. When we treated CLL cells from untreated patients with Bcl2 inhibitors venetoclax, S55746 and LP-118 (Bcl-2/Bcl-xl inhibitor, Newave), CLL cells showed increasing sensitivity to the Bcl2 inhibitors associated with their PNP expression (high&gtlow&gtno PNP). But a covalent and non-covalent BTKi LP-168 (Newave) cultured with CLL cells showed no difference in drug sensitivity associated with CLL PNP levels. In contrast CLL cells when treated with both venetoclax and LP-168, showed more drug sensitivity in the high PNP expressing CLL cells vs low/no PNP. These results indicate that active purine metabolism in CLL cells can contribute to differential novel agent drug responses of CLL patients. Future studies to understand the exact mechanism of how PNP relates to this differential drug sensitivity should be instructive in regard to alternate maneuvers to treat CLL. Citation Format: Sutapa Sinha, Weiguo Han, Zhiquan Wang, Kari G. Rabe, Susan L. Slager, Chantal E. McCabe, Daniel R. O'Brien, Sameer A. Parikh, Esteban Braggio, Yi Chen, Fenlai Tan, Stephen P. Anthony, Yu Chen, Bing Dai, Yue Shen, Neil E. Kay. Role of purine metabolism in CLL cell pathobiology and CLL disease progression [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 297.

Abstract 4190: Patient-derived xenograft (PDX) models with differential HER2 expression for preclinical evaluation of HER2-targeted therapies

Abstract Human epidermal growth factor receptor 2 (HER2) is a critical therapeutic target in gastric cancer. However, the varying expression levels of HER2 in patients present a significant challenge in selecting the appropriate HER2-targeted therapies. Patient-derived xenograft (PDX) models offer a valuable tool to address this clinical concern. We established a panel of PDX models derived from gastric cancer patients, each representing a distinct range of HER2 expression levels. These models were subsequently treated with HER2-targeted drugs, including Trastuzumab (Herceptin), Margetuximab, and Enhertu. Our results demonstrated differential drug responses corresponding to the varying HER2 expression levels in the PDX samples. Trastuzumab, Margetuximab, and Enhertu exhibited distinct efficacies across the HER2 expression spectrum. This underscores the significance of selecting the right therapeutic approach based on the HER2 status of individual patient. Our collection of PDX models with differential HER2 expression levels provides a robust platform for preclinical evaluation of HER2-targeted therapies. This approach not only addresses the clinical challenge of HER2 heterogeneity but also facilitates a more personalized and effective treatment strategy for gastric cancer patients. Citation Format: Xiaoliu Yang, Shiying Guo, Huiyi Wang, Xu Su, Jing Zhao, Xiang Gao, Cunxiang Ju. Patient-derived xenograft (PDX) models with differential HER2 expression for preclinical evaluation of HER2-targeted therapies [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 4190.

Abstract 4236: PDX-derived organoids (PDXO) are valuable tools to unveil the shortcomings of new anti-cancer drug candidates

Abstract Introduction: Tumor organoids are increasingly being used as predictive preclinical cancer models, as they reflect the original tumor features and patient drug responses. However, systematic comparisons between organoids and traditional 2D cell lines or 3D spheroids are lacking. Method: We established over 30 PDX-derived organoid (PDXO) models with KRAS mutations and tested three inhibitors targeting the KRAS pathway: VS-6766(RAF/MEK inhibitor), Trametinib (MEK inhibitor), and MRTX1133 (a Phase II drug targeting KRASG12D) against these models. Results: IC50 results indicated that most models responded to treatment. For some cell lines we detected differential drug responses in 2D vs. 3D testing with 3Dspheroids being more sensitive to inhibitors than 2D cell lines (on average ~10 fold). PDXO models exhibited greater individual differences in drug response, with a subset of models demonstrating no sensitivity to MRTX1133. This is consistent with published results showing that some KRASG12D-mutant PDX models were less sensitive to MRTX11331. Similarly, the clinical trial data for the KRASG12C inhibitor Adagrasib revealed distinctions in the response of patients2. Further analysis with WES (whole exome sequencing) and RNA-sequencing identified potential genotypic mutations and differential expressions of signaling pathways related to drug resistance. Subsequent drug combination testing showed that targeting these pathways could enhance the MRTX1133 efficacy in the resistant PDXO models. Summary: Our research confirms that drug testing on organoids predicts responses in mouse models and clinical trials. In combination with multi-omics and bioinformatics analysis, the platform can be used for evaluating drug resistances, identifying new targets, developing new drug combination therapies, and ultimately improving the creation of new cancer therapeutics. Citation Format: Yuhui Wang, Lin Feng, Han Liu, Junwen Zhang, Kaiqiang Hu, Pengwei Pan, Fang He. PDX-derived organoids (PDXO) are valuable tools to unveil the shortcomings of new anti-cancer drug candidates [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 4236.

An inflamed tumor cell subpopulation promotes chemotherapy resistance in triple negative breast cancer

Individual cancers are composed of heterogeneous tumor cells with distinct phenotypes and genotypes, with triple negative breast cancers (TNBC) demonstrating the most heterogeneity among breast cancer types. Variability in transcriptional phenotypes could meaningfully limit the efficacy of monotherapies and fuel drug resistance, although to an unknown extent. To determine if transcriptional differences between tumor cells lead to differential drug responses we performed single cell RNA-seq on cell line and PDX models of breast cancer revealing cell subpopulations in states associated with resistance to standard-of-care therapies. We found that TNBC models contained a subpopulation in an inflamed cellular state, often also present in human breast cancer samples. Inflamed cells display evidence of heightened cGAS/STING signaling which we demonstrate is sufficient to cause tumor cell resistance to chemotherapy. Accordingly, inflamed cells were enriched in human tumors taken after neoadjuvant chemotherapy and associated with early recurrence, highlighting the potential for diverse tumor cell states to promote drug resistance.

Personalization of Therapy in High-Grade Serous Tubo-Ovarian Cancer-The Possibility or the Necessity?

High-grade serous tubo-ovarian cancer (HGSTOC) is the most lethal tumor of the female genital tract. The foregoing therapy consists of cytoreduction followed by standard platinum/taxane chemotherapy; alternatively, for primary unresectable tumors, neo-adjuvant platinum/taxane chemotherapy followed by delayed interval cytoreduction. In patients with suboptimal surgery or advanced disease, different forms of targeted therapy have been accepted or tested in clinical trials. Studies on HGSTOC discovered its genetic and proteomic heterogeneity, epigenetic regulation, and the role of the tumor microenvironment. These findings turned attention to the fact that there are several distinct primary tumor subtypes of HGSTOC and the unique biology of primary, metastatic, and recurrent tumors may result in a differential drug response. This results in both chemo-refractoriness of some primary tumors and, what is significantly more frequent and destructive, secondary chemo-resistance of metastatic and recurrent HGSTOC tumors. Treatment possibilities for platinum-resistant disease include several chemotherapeutics with moderate activity and different targeted drugs with difficult tolerable effects. Therefore, the question appears as to why different subtypes of ovarian cancer are predominantly treated based on the same therapeutic schemes and not in an individualized way, adjusted to the biology of a specific tumor subtype and temporal moment of the disease. The paper reviews the genomic, mutational, and epigenetic signatures of HGSTOC subtypes and the tumor microenvironment. The clinical trials on personalized therapy and the overall results of a new, comprehensive approach to personalized therapy for ovarian cancer have been presented and discussed.

PIM1 Point Mutations Increase Migration of Diffuse Large B-Cell Lymphoma (DLBCL) Cells

PIM1 serine-threonine kinase is known proto-oncogene, highly expressed in lymphoid malignancies. It regulates crucial processes for the cancer cell, like proliferation, apoptosis, metabolism or migration. In DLBCLs, PIM1 gene is a target of somatic hypermutation and one of the most frequently mutated genes in DLBCL patients. PIM1 mutations are more frequent in ABC-type tumors, which have worse survival prognosis than GCB-type, and often co-occur with mutations in MYD88 and CD79B. Analyses of the available clinical data show that the most significant differences between the groups of DLBCL patients with or without PIM1 mutations are tumor mutational burden, age at diagnosis and extranodal (testicular) involvement. In line with this finding, PIM1, MYD88 and CD79B mutations have also been reported to be highly prevalent in extranodal B cell lymphomas, localized in central nervous system (PCNSL), testicles (PTL) or intravascular space (IVLBCL). Our goal was to assess the role of the most common PIM1 point mutations in the biology and pathogenesis of DLBCL cells. The HBL-1 cell line was chosen as a model of MYD88 L265P-positive ABC-DLBCL subtype. PIM1 knock-out was performed using CRISPR/Cas9 method. Sequences of wild type PIM1, kinase-dead PIM1K67M, serving as a an inactive kinase control, and 7 most frequent mutants (PIM1G28D, PIM1E70K, PIM1P81L, PIM1S97N, PIM1P125A, PIM1L164F, PIM1L184F) were reintroduced to the HBL-1 PIM1 KO cells using lentiviral vectors. PIM1 mutations did not affect the proliferation of DLBCL cells and did not increase resistance to doxorubicin, excluding the proliferation rate or treatment resistance as a cause of the poor prognosis associated with PIM1 mutations. We performed RNA-seq analysis of the HBL-1-PIM1-WT and HBL-1-PIM1-mutants. The most upregulated pathways in PIM1 mutants (including PIM1K67M) were those related to Interferon gamma, IL-15, STAT3, cMET and semaphorin-plexin signaling (involved in proliferation, actin dynamics and migration of cancer cells). We also found that PIM1 mutants universally overexpress cMET oncogene. Moreover, gene set and pathway enrichment analyses indicated that the PIM1-mutant cells exhibit features associated with altered actin polymerization, RHO GTPases and cell membrane dynamics, suggesting the increased migratory potential of the cells and their propensity to spread to extranodal sites. Higher surface level of cMET in PIM1 mutant cells was confirmed using FACS analysis. Since cMET and CXCR4 cooperate in signaling and trigger AKT/mTOR, which is required for CXCR4-mediated cell motility, we evaluated whether PIM1 mutant cells would exhibit increased phosphorylation of AKT. In line with this hypothesis, we noted higher pAKT and pERK1/2 in PIM1 mutant cells than in PIM1 WT cells. Finally, in transwell assays, PIM1 mutant cells exhibited markedly increased migratory potential. Taken together, these studies indicate that PIM1 mutants are not likely associated with differential drug responses, but rather facilitate tumor dissemination and are thus associated with inferior prognosis in DLBCL patients harboring PIM1 mutations.

Differential drug response in pulmonary arterial hypertension: The potential for precision medicine.

Pulmonary arterial hypertension (PAH) is a rare, complex, and deadly cardiopulmonary disease. It is characterized by changes in endothelial cell function and smooth muscle cell proliferation in the pulmonary arteries, causing persistent vasoconstriction, resulting in right heart hypertrophy and failure. There are multiple drug classes specific to PAH treatment, but variation between patients may impact treatment response. A small subset of patients is responsive to pulmonary vasodilators and can be treated with calcium channel blockers, which would be deleterious if prescribed to a typical PAH patient. Little is known about the underlying cause of this important difference in vasoresponsive PAH patients. Sex, race/ethnicity, and pharmacogenomics may also factor into efficacy and safety of PAH-specific drugs. Research has indicated that endothelin receptor antagonists may be more effective in women and there have been some minor differences found in certain races and ethnicities, but these findings are muddled by the impact of socioeconomic factors and a lack of representation of non-White patients in clinical trials. Genetic variants in genes such as CYP3A5, CYP2C9, PTGIS, PTGIR, GNG2, CHST3, and CHST13 may influence the efficacy and safety of certain PAH-specific drugs. PAH research faces many challenges, but there is potential for new methodologies to glean new insights into PAH development and treatment.

SpaRx: elucidate single-cell spatial heterogeneity of drug responses for personalized treatment.

Spatial cellular authors heterogeneity contributes to differential drug responses in a tumor lesion and potential therapeutic resistance. Recent emerging spatial technologies such as CosMx, MERSCOPE and Xenium delineate the spatial gene expression patterns at the single cell resolution. This provides unprecedented opportunities to identify spatially localized cellular resistance and to optimize the treatment for individual patients. In this work, we present a graph-based domain adaptation model, SpaRx, to reveal the heterogeneity of spatial cellular response to drugs. SpaRx transfers the knowledge from pharmacogenomics profiles to single-cell spatial transcriptomics data, through hybrid learning with dynamic adversarial adaption. Comprehensive benchmarking demonstrates the superior and robust performance of SpaRx at different dropout rates, noise levels and transcriptomics coverage. Further application of SpaRx to the state-of-the-art single-cell spatial transcriptomics data reveals that tumor cells in different locations of a tumor lesion present heterogenous sensitivity or resistance to drugs. Moreover, resistant tumor cells interact with themselves or the surrounding constituents to form an ecosystem for drug resistance. Collectively, SpaRx characterizes the spatial therapeutic variability, unveils the molecular mechanisms underpinning drug resistance and identifies personalized drug targets and effective drug combinations.

Influence of Metabolic, Transporter, and Pathogenic Genes on Pharmacogenetics and DNA Methylation in Neurological Disorders.

Pharmacogenetics and DNA methylation influence therapeutic outcomes and provide insights into potential therapeutic targets for brain-related disorders. To understand the effect of genetic polymorphisms on drug response and disease risk, we analyzed the relationship between global DNA methylation, drug-metabolizing enzymes, transport genes, and pathogenic gene phenotypes in serum samples from two groups of patients: Group A, which showed increased 5-methylcytosine (5mC) levels during clinical follow-up, and Group B, which exhibited no discernible change in 5mC levels. We identified specific SNPs in several metabolizing genes, including CYP1A2, CYP2C9, CYP4F2, GSTP1, and NAT2, that were associated with differential drug responses. Specific SNPs in CYP had a significant impact on enzyme activity, leading to changes in phenotypic distribution between the two patient groups. Group B, which contained a lower frequency of normal metabolizers and a higher frequency of ultra-rapid metabolizers compared to patients in Group A, did not show an improvement in 5mC levels during follow-up. Furthermore, there were significant differences in phenotype distribution between patient Groups A and B for several SNPs associated with transporter genes (ABCB1, ABCC2, SLC2A9, SLC39A8, and SLCO1B1) and pathogenic genes (APOE, NBEA, and PTGS2). These findings appear to suggest that the interplay between pharmacogenomics and DNA methylation has important implications for improving treatment outcomes in patients with brain-related disorders.

Abstract A043: Identifying tumor heterogeneity and drug sensitivity in primary prostate cancer towards personalized medicine

Abstract Introduction: Prostate cancer (PCa) is a highly heterogeneous disease with multiple and distinct cancer foci within the same prostate gland. We hypothesize that heterogeneous lesions, may be linked to different functional properties e.g. differential drug response sensitivity. Here we investigate which histopathological and molecular properties are associated with ability to maintain PCa cells as ex vivo organoid cultures and possibly specific drug responses. Methods: To simultaneously assess the histopathology, genetic profile and organoid drug sensitivity, we employed mirror biopsies for FFPE and cell preparations. Four cores of prostate tissue from radical prostatectomies (N=13) were used for generating patient-derived organoids (PDOs). Targeted genomic sequencing was performed on PDOs and their parental FFPE tissues. Drug response was evaluated by ATP-based viability assay after treatment with standard-of-care (AR inhibitors), and approved compounds for other malignancies (DNA synthesis, receptor tyrosine kinase (RTK) and mTOR inhibitors). RNA sequencing was performed on the parental cores. Associations among mutations, transcriptomic profile and PDO responses were being further explored using machine learning (ML) algorithms towards drug response prediction. Results: Histologically heterogeneous cores with different Gleason Score (GS range 6 to 9) per prostate were found in 76% of cases (N=10/13). A fraction of 78% of tumor-containing cores (N=22/28) and 66% of benign cores (N=16/24) gave rise to PDOs, showing a high formation efficiency. PCa somatic mutations were found in 19/32 cores, 11 cores of which shared mutations with their matching PDOs. The transcriptomic profile of each case was overall preserved among different cores. Drug responses in PDOs revealed not only inter- but also intra-patient heterogeneity with only 2 patient cases (N=2/13) having positive correlation within the different cores of the same case (Pearson’s R =0.58, 0.72 based on z-score viability). Instead, RTK inhibitors, Crizotinib and Ponatinib, showed high efficacy in the majority of cases (p<0.01 over vehicle, N=29/32 and N=30/32, respectively). Statistically significant correlations were found among 8 genomic mutations (mainly FGFR1, JAK2 and cell cycle members) and sensitivity to 5 drug compounds. Different features were tested for ML model, with RNA-seq outperforming the rest features; on average 260-1800 genes per drugs were selected for the drug prediction. ML linear regression models showed high Pearson’s correlation (R>0.8) between predicted and observed drug response values in 13/13 patients and 10/11 compounds tested. Conclusions: The majority of primary PCa cases showed genetic and histopathological multifocality, representing a highly heterogeneous cohort. PDOs recapitulated the genetic signature of the parental tissues. Drug responses of PDOs did not follow patient-specific patterns but rather revealed high inter- and intra-patient heterogeneity. Therapy response could be predicted based on transcriptomic profile for personalized treatment decision. Citation Format: Juening Kang, Sofia Karkampouna, Katja Ovchinnikova, Panagiotis Chouvardas, George Thalmann, Marianna Kruithof-de Julio. Identifying tumor heterogeneity and drug sensitivity in primary prostate cancer towards personalized medicine [abstract]. In: Proceedings of the AACR Special Conference: Advances in Prostate Cancer Research; 2023 Mar 15-18; Denver, Colorado. Philadelphia (PA): AACR; Cancer Res 2023;83(11 Suppl):Abstract nr A043.

Abstract IA014: Drug sensitivity of multifocal primary prostate cancer

Abstract Prostate cancer (PCa) is a highly heterogeneous disease with multiple and distinct cancer foci within the same prostate gland. We hypothesize that heterogeneous lesions, in terms of genomic aberrations and tumour staging, may be linked to different functional properties e.g. differential drug response sensitivity. We investigate which histopathological and molecular properties are associated with ability to maintain PCa cells as ex vivo organoid cultures and possibly specific drug responses. Interestingly, the majority of primary PCa cases showed genetic and histopathological multifocality, representing a highly heterogeneous cohort. PDOs recapitulated the genetic signature of the parental tissues. Drug responses of PDOs did not follow patient-specific patterns but rather revealed high inter- and intra-patient heterogeneity. Therapy response could be predicted based on transcriptomic profile for personalized treatment decision. The transcriptomic profile of each case was overall preserved among different cores. Drug responses in PDOs revealed not only inter- but also intra-patient heterogeneity with only 2 patient cases having positive correlation within the different cores of the same case. Statistically significant correlations were found among 8 genomic mutations and sensitivity to 5 drug compounds. Different features were tested for ML model, with RNA-seq outperforming the rest features; on average 260-1800 genes per drugs were selected for the drug prediction. ML linear regression models showed high Pearson’s correlation between predicted and observed drug response values. Citation Format: Marianna Kruithof-de Julio, Juening Kang, Sofia Karkampouna, Katja Ovchinnikova, Panagiotis Chouvardas, George N Thalmann. Drug sensitivity of multifocal primary prostate cancer [abstract]. In: Proceedings of the AACR Special Conference: Advances in Prostate Cancer Research; 2023 Mar 15-18; Denver, Colorado. Philadelphia (PA): AACR; Cancer Res 2023;83(11 Suppl):Abstract nr IA014.

Abstract 5926: High dimensional morphology analysis reveals new insights in melanoma cell heterogeneity

Abstract Melanomas are the deadliest skin cancers, in part due to cellular plasticity and heterogeneity within the tumors. These characteristics have made a deeper understanding of melanomas challenging. Classically, melanoma cells are characterized with a limited set of protein biomarkers. Gene expression signatures and mutational analysis (e.g., BRAF and NRAS genotyping) can provide a more detailed view of heterogeneity but may not translate to readily available biomarkers for functional studies. The Deepcell platform enables multi-dimensional morphology analysis and enrichment of unlabeled single cells using artificial intelligence (AI), advanced imaging, and microfluidics, enabling high resolution profiling of population heterogeneity. Label-free multi-dimensional morphology analysis may have higher resolution than a limited set of protein biomarkers, minimizes perturbation to the transcriptome, and reduces cell handling steps. We used patient-derived cell lines and dissociated biopsy samples to train a Deepcell AI model to identify and sort for melanoma cells based on morphology alone. The model was tested on metastatic melanoma biopsies, with identification and enrichment of melanoma cells verified by various downstream assays, including scRNASeq. In addition to melanoma populations, the AI model classified various cells of the microenvironment, such as stromal cells and immune subtypes, based on morphology only. To further characterize tumor heterogeneity, we imaged >25 patient-derived melanoma cell lines representing melanocytic, mesenchymal, and intermediate phenotypic states on the Deepcell platform. Morphology analysis of these images revealed distinct clusters of cells for each phenotype, indicating that there are morphological differences associated with each state. We developed a random forest (RF) classifier to identify the top differential morphological features between the different cell lines, thereby providing a label-free means of phenotyping melanoma samples. The morphology analysis of the cell lines uncovered significant variability in pigmentation; an RF classifier distinguished between pigmented vs non-pigmented cells with >90% accuracy. Pigmentation is a hallmark of melanoma cells, and it has been associated with the melanocytic phenotype and differential drug response in vitro. However, there is not currently a robust method to profile and study pigmentation in live cells. We further investigated this observation by correlating morphological profiles, molecular, and functional information with the level of cell pigmentation. The Deepcell platform presents a new method for sorting and characterizing cellular heterogeneity using morphology, including pigmentation status. As such, multi-dimensional morphology analysis will bolster the understanding of complex melanoma states and tumor microenvironment, particularly in patient derived biopsies. Citation Format: Evelyn Lattmann, Aizhan Tastanova, Andreja Jovic, Kiran Saini, Tiffine Pham, Christian Corona, Jeanette Mei, Michael Phelan, Stephane C. Boutet, Ryan Carelli, Kevin B. Jacobs, Julie Kim, Manisha Ray, Chassidy Johnson, Nianzhen Li, Mahyar Salek, Maddison Masaeli, Mitchell P. Levesque. High dimensional morphology analysis reveals new insights in melanoma cell heterogeneity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5926.

Abstract 6256: Inhibition of class IIa HDACs potentiates MYC inhibitor-driven cytotoxicity by inducing MYC depletion and oxidative stress in non-small cell lung cancer

Abstract Lung cancer is the most common cause of cancer mortality worldwide and non-small cell lung cancer (NSCLC) accounts for approximately 85% of all lung cancers. Dysregulation and/or overexpression of MYC are widely implicated in NSCLC, which suggests that MYC may be a promising therapeutic target for the treatment of NSCLC. Recently, two direct MYC inhibiting agents with improved in vivo efficacy and tolerability, MYCi975 and Omomyc, have been developed. To define new drug strategies that could potentiate the therapeutic effects of MYC inhibitors, transcriptome datasets from MYCi975 and Omomyc studies were reanalyzed. These data revealed the induction of two class IIa histone deacetylases (HDACs), HDAC5 and HDAC9, upon MYC inhibition. Importantly, class IIa HDACs are involved in cancer proliferation, aggressiveness, and prognosis. In addition, novel agents that selectively inhibit class IIa HDACs have demonstrated promising anti-tumor efficacy; thus, suggesting potential therapeutic benefits from dual targeting of MYC and class IIa HDACs. We assessed the treatment efficacy of MYCi plus class IIa HDACi across 18 NSCLC cell lines, 10 of which demonstrated substantial reduction of cell viability upon combination treatment. Querying of driver mutation spectra associated with differential drug response in our cell line panel defined that EGFR mutant cell lines exhibited resistance, while STK11 or Ras mutant cell lines were sensitive to our drug paradigm. Gene set enrichment analysis comparing the transcriptomes of sensitive versus resistant cell lines revealed that MYC Targets, Oxidative Phosphorylation, and Reactive Oxygen Species (ROS) pathways were activated in combination treatment responsive cell lines. RNA sequencing on treated cell lines identified large-scale transcriptional shifts facilitated by combination treatment, including suppression of MYC, cell cycle, and mitochondrial pathways. Furthermore, G1/S arrest and elevated mitochondrial ROS levels in combination drug-treated cells were confirmed using flow cytometry. Concordant with the role of MYC as a key cell cycle regulator, MYC protein levels were decreased in the combination treatment group as compared to the vehicle or mono-treatment groups. Importantly, both MYC overexpression and ROS scavenger treatment partially rescued the reduction of cell viability by combination treatment, suggesting both MYC depletion and ROS elevation as contributors to therapeutic efficacy driven by combination treatment. Expanding these studies to in vivo models, we discern that combination MYC and class IIa HDAC inhibition significantly reduced tumor burden in a patient-derived xenograft model of human NSCLC. In summary, we define here a novel drug paradigm combining MYC and class IIa HDAC inhibitors, which potentiates anti-tumor efficacy in NSCLC via MYC depletion and oxidative stress. Citation Format: Jina Park, Ying-Yu Chen, Jennie Cao, Michelle Vaz, Ray-Whay C. Yen, Stephen B. Baylin, Michael J. Topper. Inhibition of class IIa HDACs potentiates MYC inhibitor-driven cytotoxicity by inducing MYC depletion and oxidative stress in non-small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6256.