Drug-resistant Subpopulations Research Articles

Sequencing by binding rivals SMOR error-corrected sequencing by synthesis technology for accurate detection and quantification of minor (< 0.1%) subpopulation variants

BackgroundDetecting very minor (< 1%) subpopulations using next-generation sequencing is a critical need for multiple applications, including the detection of drug resistant pathogens and somatic variant detection in oncology. A recently available sequencing approach termed ‘sequencing by binding (SBB)’ claims to have higher base calling accuracy data “out of the box.” This paper evaluates the utility of using SBB for the detection of ultra-rare drug resistant subpopulations in Mycobacterium tuberculosis (Mtb) using a targeted amplicon assay and compares the performance of SBB to single molecule overlapping reads (SMOR) error corrected sequencing by synthesis (SBS) data.ResultsSBS displayed an elevated error rate when compared to SMOR error-corrected SBS and SBB techniques. SMOR error-corrected SBS and SBB technologies performed similarly within the linear range studies and error rate studies.ConclusionsWith lower sequencing error rates within SBB sequencing, this technique looks promising for both targeted and unbiased whole genome sequencing, leading to the identification of minor (< 1%) subpopulations without the need for error correction methods.

Abstract 1225: Novel cellular barcoding to dissect melanoma heterogeneity and drug resistance

Abstract Melanoma is the most common cause of death in skin cancer. While the development of targeted therapies (MAPK pathway inhibitors) led to a substantial improvement in overall survival of patients with melanoma harboring the BRAFV600E mutation, approximately 40% of treated patients acquire resistance and experience tumor recurrence after one year. Melanoma drug resistance is mediated by drug-tolerant persister (DTP) cell subpopulations present in tumors. DTP cells are either intrinsically rare sub-populations pre-existing prior to therapies, or adaptive sub-populations that acquire genetic and epigenetic alterations during treatments. Our lab has established six PDX models that responded to the treatment of BRAF/MEK inhibitor combination then relapsed in six to 40 weeks. We combined cell lineage barcoding and single-cell transcriptomics to trace the emergence of DTP cells in melanoma recurrence. The recent development of cellular barcoding facilitates the labelling of tens to millions of cancer clones and enables the identification of the complex mechanisms associated with clonal fate in response to therapy and in different microenvironments. We have constructed a library of approximately 15 million barcodes into a lentiviral vector. Melanoma cells were infected with the barcode library to ensure each cell carried a unique barcode. Labelled melanoma cells were injected into NSG mice, which were then treated with BRAF/MEK inhibitors, and they developed drug resistance with prolonged treatments. Treated tumors were harvested at different timepoints until relapse. The barcodes are localized close to the polyA tail of the expressed mRNA, the 3’ end sequence of which could be retrieved simultaneously through single-cell RNA sequencing (scRNAseq). Thus, we can trace the clonal information from the relapsed tumor back to earlier timepoints such as the treatment naive tumor and minimal residual disease (MRD) stage. Our data showed that the diversity of barcodes in MRD stage had no significance compared to treatment naive tumor, while the diversity of barcodes in the relapsed tumor decreased around 10-fold from the MRD stage. The most dominant sub-populations in MRD arose from minor sub-populations in the treatment naive tumor, while most of the dominant sub-populations in the relapsed tumor were daughter cells from minor sub-populations in MRD stage. The top three sub-populations dominated 25% of the relapsed tumor. The three dominant drug-resistant sub-populations shared a similar phenotype shown by scRNAseq clusters. The data indicate that the heterogeneity of melanoma is maintained in the early treatment stage but is lost in acquired resistance. And the lineages of DTP cells change continuously under prolonged BRAF/MEKi drug pressure. Citation Format: Haiyin Li, Yeqing Chen, Jessica Kaster, Nazifa Promi, Meenhard Herlyn. Novel cellular barcoding to dissect melanoma heterogeneity and drug resistance [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 1225.

Abstract 1214: Investigating therapeutic strategies to promote immune rejection of KRASG12C inhibitor-resistant subpopulations in lung cancer

Abstract Oncogenic KRAS signaling not only promotes progression and survival of cancer cells, but it can also play a major role in suppressing anti-tumor immunity through several mechanisms, including secretion of cytokines, reduction of antigen presentation and suppression of tumor-intrinsic interferon responses. Consequently, treatment with KRASG12C inhibitors alleviates oncogenic KRAS driven immune suppression, resulting in a profound remodeling of the tumor microenvironment (TME). In immunogenic mouse models, these changes can lead to the generation of some complete responses which are dependent on the engagement of the immune system. In this project we aim to investigate whether the induction of immune responses triggered by KRASG12C inhibition can effectively target inhibitor-resistant subclones. To achieve this, we mimic the development of drug resistance by combining reporter-traced isogenic KRASG12C and KRASG12D mutant lung cancer cells, where the KRASG12D mutant cells are inherently resistant to KRASG12C inhibitors. Growth of resistant cells was monitored via in vivo luciferase imaging and end point flow cytometry. KRASG12C inhibition as monotherapy, either with the active-state KRASG12C inhibitor RMC-4998 or the inactive-state inhibitor adagrasib, led to a proliferative advantage of the drug-resistant subpopulation, suggesting that any immune response to KRASG12C inhibition in the bulk tumor population was insufficient to target the resistant cell subclones. To investigate if immune mediated elimination of resistant cells could be achieved using combinations, we assessed two strategies commonly evaluated in clinical trials with KRASG12C inhibitors: anti-PD1 blockade and SHP2 inhibition. Of note, KRASG12D mutant cells do not respond to these therapies when grown subcutaneously. Treatment of RMC-4998 in combination with either anti-PD1 or the SHP2 inhibitor RMC-4550 was able to induce complete eradication of both KRASG12C and KRASG12D mutant lung cancer cells, despite the resistant cells being insensitive to these therapies when treated in the absence of sensitive cells. Furthermore, both combinations induced immune memory towards the resistant cells. These long-term effects were dependent on the immune system as they were not observed in immune deficient mice. Immune profiling of treated tumors revealed that both combinations can result in a more profound remodeling of the TME and potentiate the immune responses. Overall, our preclinical results demonstrate that the anti-tumor responses generated by the combination of KRASG12C inhibitors with SHP2 inhibition and/or immune checkpoint blockade can result in the bystander immune mediated killing of subclones of KRASG12C inhibitor resistant cells, providing a paradigm for the development of therapeutic combinations that may be more able to counter the development of inhibitor resistance. Citation Format: Mona Tomaschko, Christopher Moore, Claire E. Pillsbury, Kangbo Ng, Sophie de Carne, Sareena Rana, Andrea de Castro, Panayiotis Anastasiou, Miriam Molina-Arcas, Julian Downward. Investigating therapeutic strategies to promote immune rejection of KRASG12C inhibitor-resistant subpopulations in lung cancer [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 1214.

Modeling 5-FU-Induced Chemotherapy Selection of a Drug-Resistant Cancer Stem Cell Subpopulation.

(1) Background: Cancer stem cells (CSCs) are a subpopulation of cells in a tumor that can self-regenerate and produce different types of cells with the ability to initiate tumor growth and dissemination. Chemotherapy resistance, caused by numerous mechanisms by which tumor tissue manages to overcome the effects of drugs, remains the main problem in cancer treatment. The identification of markers on the cell surface specific to CSCs is important for understanding this phenomenon. (2) Methods: The expression of markers CD24, CD44, ALDH1, and ABCG2 was analyzed on the surface of CSCs in two cancer cell lines, MDA-MB-231 and HCT-116, after treatment with 5-fluorouracil (5-FU) using flow cytometry analysis. A machine learning model (ML)-genetic algorithm (GA) was used for the in silico simulation of drug resistance. (3) Results: As evaluated through the use of flow cytometry, the percentage of CD24-CD44+ MDA-MB-231 and CD44, ALDH1 and ABCG2 HCT-116 in a group treated with 5-FU was significantly increased compared to untreated cells. The CSC population was enriched after treatment with chemotherapy, suggesting that these cells have enhanced drug resistance mechanisms. (4) Conclusions: Each individual GA prediction model achieved high accuracy in estimating the expression rate of CSC markers on cancer cells treated with 5-FU. Artificial intelligence can be used as a powerful tool for predicting drug resistance.

Next generation antibiotic combinations to combat pan-drug resistant Klebsiella pneumoniae

Antimicrobial resistance has emerged as one of the leading public health threats of the twenty-first century. Gram-negative pathogens have been a major contributor to the declining efficacy of antibiotics through both acquired resistance and tolerance. In this study, a pan-drug resistant (PDR), NDM-1 and CTX-M-15 co-producing isolate of K. pneumoniae, CDC Nevada, (Kp Nevada) was exposed to the clinical combination of aztreonam + ceftazidime/avibactam (ATM/CAZ/AVI) to overcome metallo-β-lactamases. Unexpectedly, the β-lactam combination resulted in long filamentous cell formation induced by PBP3 inhibition over 168 h in the hollow fiber infection model experiments with eventual reversion of the total population upon drug removal. However, the addition of imipenem to the two drug β-lactam combination was highly synergistic with suppression of all drug resistant subpopulations over 5 days. Scanning electron microscopy and fluorescence microscopy for all imipenem combinations in time kill studies suggested a role for imipenem in suppression of long filamentous persisters, via the formation of metabolically active spheroplasts. To complement the imaging studies, salient transcriptomic changes were quantified using RT-PCR and novel cassette assay evaluated β-lactam permeability. This showed significant upregulation of both spheroplast protein Y (SPY), a periplasmic chaperone protein that has been shown to be related to spheroplast formation, and penicillin binding proteins (PBP1, PBP2, PBP3) for all combinations involving imipenem. However, with aztreonam alone, pbp1, pbp3 and spy remained unchanged while pbp2 levels were downregulated by > 25%. Imipenem displayed 207-fold higher permeability as compared with aztreonam (mean permeability coefficient of 17,200 nm/s). Although the clinical combination of aztreonam/avibactam and ceftazidime has been proposed as an important treatment of MBL Gram-negatives, we report the first occurrence of long filamentous persister formation. To our knowledge, this is the first study that defines novel β-lactam combinations involving imipenem via maximal suppression of filamentous persisters to combat PDR CDC Nevada K. pneumoniae.

Abstract B029: Investigating therapeutic strategies to promote immune rejection of KRAS G12C inhibitor-resistant sub-populations in lung cancer

Abstract Oncogenic KRAS signaling not only instigates aberrant growth in cancer cells but can further induce inhibitory effects on anti-tumor immune responses. Hence, recently developed KRAS G12C inhibitors (G12Ci) have the potential to alleviate immune suppression in the tumor microenvironment (TME) and reshape the therapy responses for patients with a KRAS G12C driver mutation. However, rewiring of oncogenic signaling circuits and acquisition of further mutations allows cancer cells to rapidly evolve drug resistance. In fact, clinical trial data from the recently approved G12Ci, adagrasib and sotorasib, showed a median progression-free survival in non-small cell lung cancer of just 7 months. In this project, we investigate how to combat G12Ci-resistant subpopulations in lung tumors by engaging an anti-tumor immune response. We mimic the development of drug resistance by combining traced isogenic G12C- and G12D-mutant lung cancer cells, where the KRAS G12D mutant cells are inherently resistant to G12Ci. By alleviating RAS-driven immune suppression and potentially inducing immunogenic cell death of G12Ci-responsive cells, we aim to further potentiate an adaptive immune response targeting the drug-resistant population. We found that G12Ci as monotherapy drives therapy resistance by giving the drug-resistant subpopulation a proliferative advantage. On the other hand, combining G12Ci with immunotherapy or a SHP2 inhibitor potentiated an adaptive immune response to induce complete eradication of both G12C and G12D KRAS mutant cancer cell populations and also immune memory towards drug-resistant KRAS G12D cells in mice. However, when repeating the combination treatment in Rag1 −/− mice, which lack B- and T-cells, there were no complete responders. Histopathological analysis of tumor sections in immune-competent mice revealed a strong T-cell infiltration in the TME of tumors treated with combination therapies. Although understanding the mechanistic changes in the TME induced by combination therapies is ongoing, these results indicate a role for the adaptive immune response in targeting G12Ci drug-resistant subpopulations. Understanding these underlying mechanisms will contribute to combating the development of drug resistance in patients by enhancing treatment regimens that promote immune-mediated destruction of drug-resistant tumor cell sub-populations. Citation Format: Mona Tomaschko, Miriam Molina-Arcas, Christopher Moore, Sareena Rana, Sophie de Carne, Panayiotis Anastasiou, Claire Pillsbury, Andrea de Castro, Julian Downward. Investigating therapeutic strategies to promote immune rejection of KRAS G12C inhibitor-resistant sub-populations in lung cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor Immunology and Immunotherapy; 2023 Oct 1-4; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Immunol Res 2023;11(12 Suppl):Abstract nr B029.

Genomic markers of drug resistance in Mycobacterium tuberculosis populations with minority variants.

Minority variants of Mycobacterium tuberculosis harboring mutations conferring resistance can become dominant populations during tuberculosis (TB) treatment, leading to treatment failure. Our understanding of drug-resistant within-host subpopulations and the frequency of resistance-conferring mutations in minority variants remains limited. M. tuberculosis sequences recovered from liquid cultures of culture-confirmed TB cases notified between January 2017 and December 2021 in New South Wales, Australia were examined. Potential drug resistance-conferring minority variants were identified using LoFreq, and mixed populations of different M. tuberculosis strains (≥100 SNPs apart) were examined using QuantTB. A total of 1831 routinely sequenced M. tuberculosis strains were included in the analysis. Drug resistance-conferring minority variants were detected in 3.5% (65/1831) of sequenced cultures; 84.6% (55/65) had majority strains that were drug susceptible and 15.4% (10/65) had majority strains that were drug resistant. Minority variants with high-confidence drug resistance-conferring mutations were 1.5 times more common when the majority strains were drug resistant. Mixed M. tuberculosis strain populations were documented in 10.0% (183/1831) of specimens. Minority variants with high-confidence drug resistance-conferring mutations were more frequently detected in mixed M. tuberculosis strain populations (2.7%, 5/183) than in single strain populations (0.6%, 10/1648; P = 0.01). Drug-resistant minority variants require monitoring in settings that implement routine M. tuberculosis sequencing. The frequency with which drug-resistant minority variants are detected is likely influenced by pre-culture requirement. Culture-independent sequencing methods should provide a more accurate reflection of drug-resistant subpopulations.

Impact of Baloxavir Resistance-Associated Substitutions on Influenza Virus Growth and Drug Susceptibility.

Baloxavir marboxil (baloxavir) is a recently FDA-approved influenza virus polymerase acidic (PA) endonuclease inhibitor. Several PA substitutions have been demonstrated to confer reduced susceptibility to baloxavir; however, their impacts on measurements of antiviral drug susceptibility and replication capacity when present as a fraction of the viral population have not been established. We generated recombinant A/California/04/09 (H1N1)-like viruses (IAV) with PA I38L, I38T, or E199D substitutions and B/Victoria/504/2000-like virus (IBV) with PA I38T. These substitutions reduced baloxavir susceptibility by 15.3-, 72.3-, 5.4-, and 54.5-fold, respectively, when tested in normal human bronchial epithelial (NHBE) cells. We then assessed the replication kinetics, polymerase activity, and baloxavir susceptibility of the wild-type:mutant (WT:MUT) virus mixtures in NHBE cells. The percentage of MUT relative to WT virus necessary to detect reduced baloxavir susceptibility in phenotypic assays ranged from 10% (IBV I38T) to 92% (IAV E199D). While I38T did not alter IAV replication kinetics or polymerase activity, IAV PA I38L and E199D MUTs and the IBV PA I38T MUT exhibited reduced replication levels and significantly altered polymerase activity. Differences in replication were detectable when the MUTs comprised ≥90%, ≥90%, or ≥75% of the population, respectively. Droplet digital PCR (ddPCR) and next-generation sequencing (NGS) analyses showed that WT viruses generally outcompeted the respective MUTs after multiple replication cycles and serial passaging in NHBE cells when initial mixtures contained ≥50% of the WT viruses; however, we also identified potential compensatory substitutions (IAV PA D394N and IBV PA E329G) that emerged and appeared to improve the replication capacity of baloxavir-resistant virus in cell culture. IMPORTANCE Baloxavir marboxil, an influenza virus polymerase acidic endonuclease inhibitor, represents a recently approved new class of influenza antivirals. Treatment-emergent resistance to baloxavir has been observed in clinical trials, and the potential spread of resistant variants could diminish baloxavir effectiveness. Here, we report the impact of the proportion of drug-resistant subpopulations on the ability to detect resistance in clinical isolates and the impact of substitutions on viral replication of mixtures containing both drug-sensitive and drug-resistant variants. We also show that ddPCR and NGS methods can be successfully used for detection of resistant subpopulations in clinical isolates and to quantify their relative abundance. Taken together, our data shed light on the potential impact of baloxavir-resistant I38T/L and E199D substitutions on baloxavir susceptibility and other biological properties of influenza virus and the ability to detect resistance in phenotypic and genotypic assays.

Supervised learning on impedance cytometry data for label-free biophysical distinction of pancreatic cancer cells versus their associated fibroblasts under gemcitabine treatment

Chemotherapy failure in pancreatic cancer patients is widely attributed to cancer cell reprogramming towards drug resistance by cancer associated fibroblasts (CAFs), which are the abundant cell type in the tumor microenvironment. Association of drug resistance to specific cancer cell phenotypes within multicellular tumors can advance isolation protocols for enabling cell-type specific gene expression markers to identify drug resistance. This requires the distinction of drug resistant cancer cells versus CAFs, which is challenging since permeabilization of CAF cells during drug treatment can cause non-specific uptake of cancer cell-specific stains. Cellular biophysical metrics, on the other hand, can provide multiparametric information to assess the gradual alteration of target cancer cells towards drug resistance, but these phenotypes need to be distinguished versus CAFs. Using pancreatic cancer cells and CAFs from a metastatic patient-derived tumor that exhibits cancer cell drug resistance under CAF co-culture, the biophysical metrics from multifrequency single-cell impedance cytometry are utilized for distinction of the subpopulation of viable cancer cells versus CAFs, before and after gemcitabine treatment. This is accomplished through supervised machine learning after training the model using key impedance metrics for cancer cells and CAFs from transwell co-cultures, so that an optimized classifier model can recognize each cell type and predict their respective proportions in multicellular tumor samples, before and after gemcitabine treatment, as validated by their confusion matrix and flow cytometry assays. In this manner, an aggregate of the distinguishing biophysical metrics of viable cancer cells after gemcitabine treatment in co-cultures with CAFs can be used in longitudinal studies, to classify and isolate the drug resistant subpopulation for identifying markers.

Abiraterone-Docetaxel scheduling for metastatic castration-resistant prostate cancer based on evolutionary dynamics.

Patients with metastatic castration-resistant prostate cancer (mCRPC) are divided into three groups based on their response to Abiraterone treatment: best responder, responder, and non-responder. In the latter two groups, successful outcomes may not be achieved due to the development of drug-resistant cells in the tumor environment during treatment. To overcome this challenge, a secondary drug can be used to control the population of drug-resistant cells, potentially leading to a longer period of disease inhibition. This paper proposes using a combination of Docetaxel and Abiraterone in some polytherapy methods to control both the overall cancer cell population and the drug-resistant subpopulation. To investigate the competition and evolution of mCRPC cancer phenotypes, as in previous studies, the Evolutionary Game Theory (EGT) has been used as a mathematical modeling of evolutionary biology concepts.

Phenotypic deconvolution in heterogeneous cancer cell populations using drug-screening data

Tumor heterogeneity is an important driver of treatment failure in cancer since therapies often select for drug-tolerant or drug-resistant cellular subpopulations that drive tumor growth and recurrence. Profiling the drug-response heterogeneity of tumor samples using traditional genomic deconvolution methods has yielded limited results, due in part to the imperfect mapping between genomic variation and functional characteristics. Here, we leverage mechanistic population modeling to develop a statistical framework for profiling phenotypic heterogeneity from standard drug-screen data on bulk tumor samples. This method, called PhenoPop, reliably identifies tumor subpopulations exhibiting differential drug responses and estimates their drug sensitivities and frequencies within the bulk population. We apply PhenoPop to synthetically generated cell populations, mixed cell-line experiments, and multiple myeloma patient samples and demonstrate how it can provide individualized predictions of tumor growth under candidate therapies. This methodology can also be applied to deconvolution problems in a variety of biological settings beyond cancer drug response.

Abstract PD4-09: PD4-09 Single cell RNA-sequencing identifies intra-tumoral cellular heterogeneity and drug-induced subpopulation shifts in Triple Negative Breast Cancer mouse models

Abstract Introduction: Triple Negative Breast Cancer (TNBC) is an aggressive disease with a poor prognosis that accounts for 10-20% of breast cancer cases worldwide. Intra-tumoral heterogeneity and tumor cell plasticity are thought to contribute to drug resistance in TNBCs. Our work aims to: 1) precisely identify the intra-tumoral heterogeneity in cellular states present within TNBC, and 2) test whether drugs can block or initiate plasticity between subpopulations to improve drug sensitivity. We hypothesize that treatment(s) induce cellular plasticity, thus causing cells to shift into resistant states that persist until treatment is removed. We further hypothesize that these resistant subpopulations give rise to new tumor outgrowths once the treatment stops. Methods: To test this, we are treating TP53-/- Genetically Engineered Mouse Model (GEMM) syngeneic transplant tumors of the basal-like TNBC phenotype with the chemotherapeutic doublet of carboplatin/paclitaxel, and targeted agents implicated in plasticity including the MEK inhibitor trametinib, a chromatin remodeling inhibitor I-BET151, and the dihydroorotate dehydrogenase inhibitor brequinar. To identify cellular subpopulations and examine their response to treatment, we performed both in vivo and in vitro drug sensitivity testing, as well as gene expression profiling using single cell RNA-sequencing (scRNAseq). Results: We have identified clear intra-tumoral heterogeneity with at least 6 distinct cell states present, including basal, mesenchymal/claudin-low, and proliferative subpopulations in vivo in most TNBC GEMM models. We performed 18 individual scRNAseq experiments on the TP53-/- 2225L GEMM transplant line with the aforementioned treatments and untreated controls in triplicate and compared subpopulation frequencies in treated versus untreated tumors. Notably, treatment with trametinib and brequinar caused the rise of two rare subpopulations (i.e. 1% to 3-4% of total tumor cells) that express genes consistent with previously described drug-tolerant persisters (DTP), which we have called “Epithelial-DTP” (Tacstd2, Krt6a, and Cryab enriched) and “Mesenchymal-DTP” (Snai2 and Sca-1 enriched). A gene signature generated from the Epithelial-DTP subpopulation predicted poor patient outcomes in neoadjuvant chemotherapy treated TNBC patients. Further, in TNBC patient-derived xenografts (PDX), these two DTP subpopulations are also present and induced by treatment to an even greater frequency. Ongoing experiments include the use of fluorescence-activated cell sorting to isolate and functionally test the tumor-initiating capabilities of these two rare cell subpopulations. In addition, many experiments are underway to identify means to therapeutically target these DTP cells, with these results to be presented. Ultimately, identifying these rare drug resistant subpopulations, and identifying means to eradicate them, could vastly improve therapeutic regimens and outcomes for patients with TNBCs. Citation Format: Cherise R. Glodowski, Kevin R. Mott, Denis Okumu, Michael P. East, Timothy C. Elston, Gary L. Johnson, Charles M. Perou. PD4-09 Single cell RNA-sequencing identifies intra-tumoral cellular heterogeneity and drug-induced subpopulation shifts in Triple Negative Breast Cancer mouse models [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr PD4-09.

Enabling Single-Cell Drug Response Annotations from Bulk RNA-Seq Using SCAD.

The single-cell RNAsequencing (scRNA-seq) quantifies the gene expression of individual cells, while the bulk RNA sequencing (bulk RNA-seq) characterizes the mixed transcriptome of cells. The inference of drug sensitivities for individual cells can provide new insights to understand the mechanism of anti-cancer response heterogeneity and drug resistance at the cellular resolution. However, pharmacogenomic information related to their corresponding scRNA-Seq is often limited. Therefore, a transfer learning model is proposed to infer the drug sensitivities at single-cell level. This framework learns bulk transcriptome profiles and pharmacogenomics information from population cell lines in a large public dataset and transfers the knowledge to infer drug efficacy of individual cells. The results suggest that it is suitable to learn knowledge from pre-clinical cell lines to infer pre-existing cell subpopulations with different drug sensitivities prior to drug exposure. In addition, the model offers a new perspective on drug combinations. It is observed that drug-resistant subpopulation can be sensitive to other drugs (e.g., a subset of JHU006 is Vorinostat-resistant while Gefitinib-sensitive); such finding corroborates the previously reported drug combination (Gefitinib + Vorinostat) strategy in several cancer types. The identified drug sensitivity biomarkers reveal insights into the tumor heterogeneity and treatment at cellular resolution.

Low c-Kit expression identifies primitive, therapy-resistant CML stem cells.

Despite the efficacy of tyrosine kinase inhibitors (TKIs) in chronic myeloid leukemia (CML), malignant long-term hematopoietic stem cells (LT-HSCs) persist as a source of relapse. However, LT-HSCs are heterogenous and the most primitive, drug-resistant LT-HSC subpopulations are not well characterized. In normal hematopoiesis, self-renewal and long-term reconstitution capacity are enriched within LT-HSCs with low c-Kit expression (c-KITlo). Here, using a transgenic CML mouse model, we found that long-term engraftment and leukemogenic capacity were restricted to c-KITlo CML LT-HSCs. CML LT-HSCs demonstrated enhanced differentiation with expansion of mature progeny following exposure to the c-KIT ligand, stem cell factor (SCF). Conversely, SCF deletion led to depletion of normal LT-HSCs but increase in c-KITlo and total CML LT-HSCs with reduced generation of mature myeloid cells. CML c-KITlo LT-HSCs showed reduced cell cycling and expressed enhanced quiescence and inflammatory gene signatures. SCF administration led to enhanced depletion of CML primitive progenitors but not LT-HSCs after TKI treatment. Human CML LT-HSCs with low or absent c-KIT expression were markedly enriched after TKI treatment. We conclude that CML LT-HSCs expressing low c-KIT levels are enriched for primitive, quiescent, drug-resistant leukemia-initiating cells and represent a critical target for eliminating disease persistence.

Multidrug resistance genes screening of pancreatic ductal adenocarcinoma based on sensitivity profile to chemotherapeutic drugs

BackgroundsPancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancer types and chemotherapeutic drug resistance is a stumbling block in improving the overall survival of PDAC patients. The nature of specific drug resistant subpopulation within pancreatic ductal adenocarcinoma is believed to be partly attributed to epithelial-mesenchymal transition (EMT) and cell stemness. Various PDAC cell lines show various degrees of resistance to chemotherapeutic agents including gemcitabine (GEM) and 5-fluorouracil (5-FU). In-depth understanding of drug resistance mechanisms and profile heterogeneities could lead to the development of novel and precise therapeutic strategies for addressing the chemo-resistant dilemma in PDAC patients.MethodsCytotoxicity assays were performed by CCK8 in ten common PDAC cell lines including AsPC-1, BxPC-3, CAPAN-1, CFPAC, HPAFII, MIA PaCa-2, PANC-1, Patu-8988, SW1990 and T3M4. RNA-seq data of the ten cell lines were downloaded from Cancer Cell Line Encyclopedia (CCLE) database and subsequently analyzed for differentially expressed genes (DEGs). Based on first-line chemotherapy regimens of PDAC, DEGs between resistant and sensitive cell lines were validated by qRT-PCR. Enriched pathways of differentially expressed genes between the resistant and sensitive cell lines were acquired by Metascape database.ResultsWe found that the top two toxic drugs for PDAC cell lines were paclitaxel (PTX) and GEM. Among the ten PDAC cell lines, SW1990 was the most resistant PDAC cell line with the highest IC50 levels for three drugs, while MIA PaCa-2 and BxPC-3 were the most sensitive PDAC cell lines. Differential expression analysis revealed the highest number of DEGs associated with cisplatin (CIS) sensitivity up to 642 genes, of which 181 genes were upregulated and 461 genes were downregulated in CIS-resistant cell lines. The least number of DEGs are associated with GEM sensitivity, of which 37 genes were highly expressed in GEM-resistant PDAC cell lines and 25 genes were lowly expressed. Enrichment analysis of the DEGs revealed that pathways associated with drug resistance were mainly extracellular matrix and cell–cell junction related pathways.ConclusionsPDAC cell lines showed diverse sensitivities to commonly used chemotherapeutic agents, which was caused by differential gene expression between the resistant and sensitive cell lines. The heterogeneity and its associated genes were enriched in extracellular matrix and cell–cell junction related pathways. Our study first portrayed the sensitivity profile to chemotherapeutic drugs of PDAC, which would benefit the chemoresistance mechanism study by reemphasizing the vital role of extracellular matrix and cell–cell junction related pathways and helping the selection of suitable PDAC cell lines.

Label-Free Quantitative Proteomics Analysis of Adriamycin Selected Multidrug Resistant Human Lung Cancer Cells.

The development of drug resistance in lung cancer is a major clinical challenge, leading to a 5-year survival rate of only 18%. Therefore, unravelling the mechanisms of drug resistance and developing novel therapeutic strategies is of crucial importance. This study systematically explores the novel biomarkers of drug resistance using a lung cancer model (DLKP) with a series of drug-resistant variants. In-depth label-free quantitative mass spectrometry-based proteomics and gene ontology analysis shows that parental DLKP cells significantly differ from drug-resistant variants, and the cellular proteome changes even among the drug-resistant subpopulations. Overall, ABC transporter proteins and lipid metabolism were determined to play a significant role in the formation of drug resistance in DKLP cells. A series of membrane-related proteins such as HMOX1, TMB1, EPHX2 and NEU1 were identified to be correlated with levels of drug resistance in the DLKP subpopulations. The study also showed enrichment in biological processes and molecular functions such as drug metabolism, cellular response to the drug and drug binding. In gene ontology analysis, 18 proteins were determined to be positively or negatively correlated with resistance levels. Overall, 34 proteins which potentially have a therapeutic and diagnostic value were identified.

Abstract 3087: The identification and characterization of FOLFOX chemotherapy resistant cell lineages in colorectal cancer organoids

Abstract Resistance to chemotherapy drugs is a well-documented issue inhibiting the treatment of a wide variety of cancers. Colorectal cancer (CRC) is the third most common neoplasm worldwide and has the third highest mortality rate. However, the longtime gold-standard FOLFOX chemotherapy regimen, consisting of 5-FU and Oxaliplatin, results in only 70% survival rates in Stage 3 CRC patients, worse in Stage 4. More recent targeted therapies have marginally improved on this number, but the fact remains that CRC represents a highly heterogeneous neoplasm and resistance to standard chemotherapeutic regimens poses a significant barrier in treating this devastating disease. There is an immediate need to better understand how this resistance arises. We hypothesize that a small number of cells with high phenotypic plasticity (HPP) are able to remain dormant during the initial chemotherapy treatment then reenter the cell cycle to cause recurrence and metastasis months or even years after treatment has concluded. Patient-derived organoids (PDOs) are a recently developed ex vivo model that allows for the study and extensive characterization of such HPP cell populations that may be found in patient tumors. We are developing and expanding various PDO populations to examine them genotypically and phenotypically on the single-cell level through RNA sequencing and high throughput imaging, respectively. By identifying these HPP cell populations, we then discover drugs that prevent the development of drug-resistant subpopulations. In the long term, we use our tumor heterogeneity profile to develop models that predict the responsiveness of tumors, including their drug-resistant HPP subpopulations, to well-documented and clinically used oncology drugs, streamlining treatment and improving survival outcomes. Citation Format: Julia M. Morris, Curtis A. Thorne. The identification and characterization of FOLFOX chemotherapy resistant cell lineages in colorectal cancer organoids [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3087.

INSP-16. Focused ultrasound-mediated blood-brain barrier disruption for the treatment of pediatric high-grade glioma

Pediatric patients with high-grade glioma (HGG), such as glioblastoma (GBM) and H3K27M-altered diffuse midline glioma (DMG) suffer from a dismal prognosis and a poor quality of life. So far, no therapeutic strategy has resulted in significant long-term survival benefit for these patients. Drug therapies have largely failed due to inadequate drug delivery to the brain as a result of the blood-brain barrier, preventing most drugs from entering the brain. Intrinsic and acquired tumor heterogeneity, with drug-resistant tumor cell subpopulations add to the therapeutic failure. Furthermore, these tumors evade the immune system by creating a highly tumor-promoting and immunosuppressive tumor immune microenvironment, which is composed of microglia and tumor-associated macrophages. Recently, microbubble-assisted, focused ultrasound-mediated blood-brain barrier disruption (FUS-BBBD) has emerged as a promising and clinically available technology to circumvent part of these problems. FUS-BBBD allows improved delivery of therapeutics (chemotherapy, small molecules, monoclonal antibodies, immunotherapies) to the brain. The technology is emerging both in preclinical and clinical pediatric neuro-oncology research, with invasive and minimally invasive clinical FUS-BBBD systems available for early phase clinical trials. How the right drugs in the optimal combination can be delivered with the best timing (pharmacokinetics) via FUS-BBBD has yet to be ascertained and is subject of in vitro and in vivo drug studies. Combining FUS-BBBD with compounds targeting microglia and tumor-associated macrophages potentially reverts the ‘immuno-cold’ tumor immune micro-environment towards an ‘immuno-hot’ state and might enhance systemic immunotherapies such as immune checkpoint inhibitor and CAR-T cell approaches. Furthermore, recent preclinical research evidenced that FUS-BBBD is able to enhance liquid biopsies by increasing the concentration of circulating biomarkers in blood. It could therefore be used for longitudinal monitoring of site-specific chemoresistance development during therapy. This presentation will provide an overview on preclinical and clinical developments in the field of FUS-BBBD-enhanced drug delivery, immune modulation and liquid biopsies. International collaboration in (pre)clinical studies with FUS-BBBD is needed to bring the field forward.

A novel CD34-specific T-cell engager efficiently depletes acute myeloid leukemia and leukemic stem cells in vitro and in vivo.

Less than a third of patients with acute myeloid leukemia (AML) are cured by chemotherapy and/or hematopoietic stem cell transplantation, highlighting the need to develop more efficient drugs. The low efficacy of standard treatments is associated with inadequate depletion of CD34+ blasts and leukemic stem cells, the latter a drug-resistant subpopulation of leukemia cells characterized by the CD34+CD38- phenotype. To target these drug-resistant primitive leukemic cells better, we have designed a CD34/CD3 bi-specific T-cell engager (BTE) and characterized its anti-leukemia potential in vitro, ex vivo and in vivo. Our results show that this CD34-specific BTE induces CD34-dependent T-cell activation and subsequent leukemia cell killing in a dose-dependent manner, further corroborated by enhanced T-cell-mediated killing at the singlecell level. Additionally, the BTE triggered efficient T-cell-mediated depletion of CD34+ hematopoietic stem cells from peripheral blood stem cell grafts and CD34+ blasts from AML patients. Using a humanized AML xenograft model, we confirmed that the CD34-specific BTE had in vivo efficacy by depleting CD34+ blasts and leukemic stem cells without side effects. Taken together, these data demonstrate that the CD34-specific BTE has robust antitumor effects, supporting development of a novel treatment modality with the aim of improving outcomes of patients with AML and myelodysplastic syndromes.

Evolutionary analysis of replicator dynamics about anti-cancer combination therapy.

The emergence and growth of drug-resistant cancer cell subpopulations during anti-cancer treatment is a major challenge for cancer therapies. Combination therapies are usually applied for overcoming drug resistance. In the present paper, we explored the evolution outcome of tumor cell populations under different combination schedules of chemotherapy and p53 vaccine, by construction of replicator dynamical model for sensitive cells, chemotherapy-resistant cells and p53 vaccine-resistant cells. The local asymptotic stability analysis of the evolutionary stable points revealed that cancer population could evolve to the population with single subpopulation, or coexistence of sensitive cells and p53 vaccine-resistant cells, or coexistence of chemotherapy-resistant cells and p53 vaccine-resistant cells under different monotherapy or combination schedules. The design of adaptive therapy schedules that maintain the subpopulations under control is also demonstrated by sequential and periodic application of combination treatment strategies based on the evolutionary velocity and evolutionary absorbing regions. Applying a new replicator dynamical model, we further explored the supportive effects of sensitive cancer cells on targeted therapy-resistant cells revealed in mice experiments. It was shown that the supportive effects of sensitive cells could drive the evolution of cell population from sensitive cells to coexistence of sensitive cells and one type of targeted therapy-resistant cells.