Understanding Of Drug Resistance Mechanisms Research Articles

Protein and metabolic profiles of tyrosine kinase inhibitors co-resistant liver cancer cells

Hepatocellular Carcinoma (HCC) patients often develop resistance to tyrosine kinase inhibitors (TKIs) like sorafenib (SR) and lenvatinib (RR). We established HCC cell lines resistant to these drugs and analyzed the correlation between protein and metabolite profiles using bioinformatics. Our analysis revealed overexpression of MISP, CHMP2B, IL-18, TMSB4X, and EFEMP1, and downregulation of IFITM3, CA4, AGR2, and SLC51B in drug-resistant cells. Differential signals are mainly enriched in steroid hormone biosynthesis, cell adhesion, and immune synapses, with metabolic pathways including cytochrome P450 drug metabolism, amino acid metabolism, and glycolysis. Proteomics and metabolomics analysis showed co-enrichment signals in drug metabolism, amino acids, glucose metabolism, ferroptosis, and other biological processes. Knocking down MISP, CHMP2B, IL-18, TMSB4X, and EFEMP1 significantly reduced drug resistance, indicating their potential as therapeutic response biomarkers. This study characterizes protein and metabolic profiles of drug-resistant HCC cells, exploring metabolite-protein relationships to enhance understanding of drug resistance mechanisms and clinical treatment.

Abstract 5839: Identification of low-dose ligand dependent drug-resistance in ALK/ROS1 positive NSCLC via CRISPR library screening

Abstract Tyrosine kinase inhibitor (TKI) therapy has displayed significant effectiveness in treating patients with anaplastic lymphoma kinase (ALK) and ROS proto-oncogene 1 (ROS1)-positive non-small cell lung cancer (NSCLC). Nonetheless, the emergence of acquired resistance in most patients presents a major challenge. Drug-tolerant persister (DTP) cells have recently gained attention as potential sources of resistance, highlighting the need for a deeper understanding of drug resistance mechanisms. To address this issue, a comprehensive genome-wide CRISPR-Cas9 knockout screening was conducted using an ALK-positive NSCLC cell line derived from pleural effusion in a patient who had not been exposed to ALK-TKI treatment. Following a 9-day ALK-TKI treatment, sequencing analysis was performed to identify sgRNAs in DTP cells. Notably, this analysis detected the involvement of tumor suppressor genes, including NF2, BAX, and ERRFI1.NF2 depletion was found to induce a substantial resistance to ALK-TKIs, and a combination therapy involving mTOR inhibitors showed promise in partially overcoming this resistance. Moreover, knockout of ERRFI1 or BAX led to an increase in DTP cells, drawing particular attention to ERRFI1, also known as MIG6, which is known for negatively regulating EGFR signaling. One intriguing discovery was that the loss of MIG6 induced resistance to ALK-TKIs when exposed to a relatively low dose of EGF, comparable to concentrations in plasma of healthy adults. This resistance was attributed to the upregulation of the MAPK and PI3K/Akt/mTOR pathways. Similar to ALK-rearranged NSCLC, ROS1 fusion-positive NSCLC cell lines also showed resistance by MIG6 knockout. Interestingly, some cell lines with reduced MIG6 expression tended to develop resistance with low-dose EGF, even without prior treatment, and overexpression of MIG6 restored sensitivity to TKIs. We further explored the potential of combination therapy, combining ALK-TKIs with anti-EGFR antibodies, and this approach effectively addressed acquired resistance in both in vivo and in vitro models. Furthermore, an analysis of clinical samples revealed that individuals resistant to ALK-TKIs displayed decreased mRNA MIG6 levels in comparison to their sensitive counterparts. Investigating the mechanisms behind MIG6 expression, we confirmed that ALK-TKI therapy suppressed MIG6 expression levels, while factors such as corticosteroid usage or exposure to hypoxia induced the upregulation of MIG6, potentially influencing the formation of DTP cells. In conclusion, this research has unveiled a novel factor contributing to resistance in ALK and ROS1-TKI therapies by activating the EGFR pathway through exposure to low-dose ligands, shedding light on potential therapeutic strategies to combat acquired resistance. Citation Format: Nobuyuki Kondo, Takahiro Utsumi, Ken Uchibori, Yasunari Miyazaki, Ryohei Katayama. Identification of low-dose ligand dependent drug-resistance in ALK/ROS1 positive NSCLC via CRISPR library screening [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 5839.

Abstract 5850: Multiomics analysis unravels tumor metabolic reprogramming and potential resistance mechanism(s) to curative therapy in TNBC

Abstract Drug resistance is the leading cause of treatment failure to completely eliminate viable tumor cells in ~40% of patients with triple negative breast cancer (TNBC). Making a major impact on the treatment and prognosis for TNBC patients requires a better understanding of drug resistance mechanism(s). Combining clinical data with high-throughput metabolomic and proteomic analyses, we probed the molecular basis for chemotherapy resistance in treatment-naive TNBC primary tumors, reflected by pathological complete response (pCR) and non-pCR after neoadjuvant chemotherapy (NAC). Metabolic profiling uncovered that glycolysis and oxidative phosphorylation (OXPHOS) co-exist in TNBC primary tumors compared to benign lesions regardless of pCR status, indicating metabolic reprogramming. However, non-pCR tumors were more enriched in OXPHOS and less in glycolysis relative to pCR tumors, pointing to the potential importance of OXPHOS in drug resistance. Moreover, parallel proteomic profiling of these same TNBC tumors supported the results from metabolic profiling, showing that OXPHOS was indeed highly enriched at the protein level, and may be regulated by SIRT5-mediated sirtuin signaling. In alignment with these findings, non-pCR tumors were abundantly enriched in immune-inhibitory metabolites that may be due to the products of SIRT5-mediated mitochondrial metabolism. Thus, these findings led me to hypothesize that SIRT5 may play an important role in chemoresistance through regulation of mitochondrial metabolism and ROS detoxification. Together, the metabolite resulted from SIRT5-mediated mitochondrial metabolism led to the suppression of immune cell infiltration in non-pCR tumors. Understanding SIRT5-mediated chemoresistance mechanism may uncover a metabolic and therapeutic vulnerability to resistant TNBCs. Citation Format: Zuen Ren, Kiran Kurmi, Robert Morris, Shakchhi Joshi, Eric Zaniewski, Johannes Kreuzer, Gabrielle Elena Gioia, Veerle I. Bossuyt, Brian N. Dontchos, Gary X. Wang, Shinn-Huey S. Chou, Laura M. Spring, Wilhelm Haas, Marcia C. Haigis, Leif W. Ellisen. Multiomics analysis unravels tumor metabolic reprogramming and potential resistance mechanism(s) to curative therapy in TNBC [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 5850.

Abstract 2827: Characterization of acute myeloid leukemia PDX models with hotspot gene mutations for therapeutic evaluation

Abstract Introduction: Acute myeloid leukemia (AML) is the most common acute type of leukemia in adults characterized by chromosomal abnormalities and gene mutations. While inhibitors have shown promise targeting FLT3 mutations, resistance to these inhibitors can emerge. Similarly, inhibitors targeting IDH1 and IDH2 mutations showed promise, yet the emergence of drug resistance poses a significant challenge. In this study, a panel of AML PDX models with multiple gene alterations was established to support the development of new therapies. Methods: The systemic AML PDX models were established using patients’ peripheral blood (PB) or bone morrow (BM) injected intravenously and expanded in vivo by using splenic tumor cells. One AML PDX model derived from patient skin was established subcutaneously. Expression of human CD45+ in PB cells for systemic models or tumor volume for the subcutaneous model was used to monitor the tumor burden. Leukemic loads (hCD45+ cells) were measured in PB, spleen (SP), and BM. Tumors were categorized following tumor immunophenotyping, histology, and RNA sequencing/Whole Exome Sequencing. For in vivo efficacy studies, animals were grouped 3-5 weeks after systemic tumor cells inoculation and treated with AC220 (1, 2 or 10 mg/kg, p.o., QD), Cytarabine (Ara-c, 2mg/kg, i.p., QD), 5-azacytidine (2mg/kg, i.p., QD), Sorafenib (10mg/kg, i.p., QD) and Gilteritinib (10 or 30mg/kg, p.o., QD). Results: Nine systemic and one subcutaneous AML PDX models carrying hotspot mutations (e.i. FLT3-ITD or TKD, IDH1-R132H and IDH2-R140Q) were established, showing comparable features to the clinic. Systemic AM8231 PDX model harboring FLT3-ITD mutation treated with AC220, a type II FLT3i, showed significant tumor burden reduction in PB at different time points and in SP and BM at termination, as well as a survival increase. Similarly in systemic model AM7577 with FLT3-ITD mutation treated with AC220, significant tumor burden reduction in PB was observed. Whereas using systemic model AM9626 (model with Sorafenib pretreatment history) with coexisting-FLT3-ITD/D835H TKD mutation, no significant efficacy was observed with AC220i, suggesting a FLT3-TKD mediated resistance mechanism. To overcome the resistance, Gilteritinib, a type I FLT3i, was tested in AM9626 and showed significant reduction of hCD45+ cells in PB compared to the control group, even at a lowest dose. As model AM9626 PDX also carries IDH1 mutation, the level of serum 2-HG correlated with the tumor burden. The functional effect of IDH1 inhibitor on the tumor inhibition and 2-HG level is under investigation. Conclusion: The results presented in this study showed the establishment of a panel of AML PDX models, including different subtypes and genomic features reflecting the clinic. Those models will support the preclinical evaluation of new treatments or combination modalities as well as a better understanding of drug resistance mechanisms. Citation Format: Qingzhi Liu, Jinxi Wang, Jinping Liu, Likun Zhang, Ludovic Bourre, Jingjing Wang. Characterization of acute myeloid leukemia PDX models with hotspot gene mutations for therapeutic evaluation [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 2827.

Abstract 535: Resistant PDO models: Unraveling drug resistance mechanisms for discovering new drug targets

Abstract Resistance to cancer treatment remains a significant obstacle in curing patients with cancer. Despite recent advancements in novel drug targets for cancer therapeutics, patients often develop treatment resistance even after initial disease remission, leading to tumor relapse. To investigate the mechanisms responsible for developing resistance to standard-of-care therapies, it is essential to gain insights into the stepwise progression leading to complete resistance. Recent research has revealed that cancer cells can evade the effects of chemotherapy and targeted therapy by entering a reversible and slow proliferation state known as the drug-tolerant persister (DTP) state. This DTP state allows cancer cells to survive drug therapy long enough for additional mechanisms of acquired drug resistance to develop. HUB Organoids® or patient-derived organoid (PDO) models are derived from patient tissues, making them more physiologically relevant than traditional cell lines. Thus, studying drug persistence and resistance in PDO models is more likely to reflect in vivo conditions. This study demonstrates the successful development of persistent and resistant CRC PDO models to standard-of-care therapies. All models were characterized using whole exome sequencing and RNA sequencing to confirm their persistent or resistant state and to identify possible pathways involved in developing therapy resistance, as well as potential new drug targets. In conclusion, developing persistent and resistant PDO models is crucial for understanding drug resistance mechanisms, enabling the development of more effective and personalized cancer treatments, and advancing our overall knowledge of how resistance develops in cancer patients. Citation Format: Yasmine Abouleila, Mayke Doorn, Roel Verkerk, Joris Maas, Carla Verissimo, Sylvia Boj. Resistant PDO models: Unraveling drug resistance mechanisms for discovering new drug targets [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 535.

Malaria’s molecular dance: Mechanism, therapies, and emerging insights

Malaria, caused by Plasmodium parasites and transmitted through Anopheles mosquitoes, remains a formidable global health challenge. This abstract provides an overview of the intricate molecular mechanisms underlying malaria pathogenesis, explores current therapeutic approaches, and highlights emerging insights that may shape future strategies for malaria control. The intricate dance between Plasmodium parasites and their human hosts begins with the mosquito’s bite, leading to the invasion of erythrocytes by Plasmodium species. We delve into the molecular mechanisms governing parasite entry and subsequent replication within host cells, shedding light on key factors such as erythrocyte surface receptors and parasite-encoded proteins critical to invasion and survival. While malaria treatment has relied heavily on antimalarial drugs, the emergence of drug resistance necessitates ongoing exploration of novel therapeutic strategies. This abstract reviews current antimalarial drug classes, their mechanisms of action, and the challenges posed by drug resistance. We also highlight promising drug candidates and innovative approaches in the pipeline, including the use of advanced molecular techniques and immunotherapies. Emerging insights from genomics, proteomics, and transcriptomics have deepened our understanding of Plasmodium biology and host-parasite interactions. We discuss the potential of these omics approaches in identifying new drug targets, understanding drug resistance mechanisms, and developing vaccines. Additionally, we examine the role of human genetics in influencing susceptibility to malaria and response to treatment. Vector control remains a critical component of malaria prevention. We touch upon emerging strategies, such as genetically modified mosquitoes and novel insecticides, in the context of integrated vector management programs. Finally, we emphasize the importance of a multifaceted approach to malaria control, combining advances in molecular biology, drug development, vector control, and public health interventions.

Isoniazid and Rifampicin Resistance-Conferring Mutations in Mycobacterium tuberculosis Isolates from South Africa.

Tuberculosis (TB), caused by Mycobacterium tuberculosis (M. tb), remains a significant global health issue, with high morbidity and mortality rates. The emergence of drug-resistant strains, particularly multidrug-resistant TB (MDR-TB), poses difficult challenges to TB control efforts. This comprehensive review and meta-analysis investigated the prevalence of and molecular insights into isoniazid (INH) and rifampicin (RIF) resistance-conferring mutations in M. tb isolates from South Africa. Through systematic search and analysis of 11 relevant studies, we determined the prevalence of gene mutations associated with RIF and INH resistance, such as rpoB, katG, and inhA. The findings demonstrated a high prevalence of specific mutations, including S450L in rpoB, and S315T, which are linked to resistance against RIF and INH, respectively. These results contribute to the understanding of drug resistance mechanisms and provide valuable insights for the development of targeted interventions against drug-resistant TB.

Developments in targeted therapy & immunotherapy-how non-small cell lung cancer management will change in the next decade: a narrative review.

The adoption of targeted therapy and immunotherapy has revolutionised the treatment landscape of non-small cell lung cancer. For early staged disease, incorporation of targeted therapy and immunotherapy has recently been demonstrated to reduce recurrence. Development of targeted therapies in advanced lung cancer is driven by advanced genomic sequencing techniques, better understanding of drug resistance mechanisms, and improved drug designs. The list of targetable molecular alteration is continuously expanding, and next generation molecular therapies have shown promise in circumventing drug resistance. Lung cancer patients may achieve durable disease control with immune checkpoint inhibitors however most patients develop immunotherapy resistance. A wide spectrum of resistance mechanisms, ranging from impaired T-cell activation, presence of coinhibitory immune checkpoints, to immunosuppressive tumour microenvironment, have been proposed. A multitude of novel immunotherapy strategies are under development to target such resistance mechanisms. This review aims to provide a succinct overview in the latest development in targeted therapy and immunotherapy for NSCLC management. We searched all original papers and reviews on targeted therapy and immunotherapy in non-small cell lung cancer (NSCLC) using PubMed in June 2022. Search terms included "non-small cell lung cancer", "targeted therapy", "immunotherapy", "EGFR", "ALK", "ROS1", "BRAF V600E", "MET", "RET", "KRAS", "HER2", "ERBB2", "NRG1", "immune checkpoint", "PD-1", "PD-L1", "CTLA4", "TIGIT", "VEGF", "cancer vaccine", "cellular therapy", "tumour microenvironment", "cytokine", and "gut microbiota". We first discuss the incorporation of targeted therapy and immunotherapy in early staged NSCLC. This includes the latest clinical data that led to the approval of neoadjuvant immunotherapy, adjuvant immunotherapy and adjuvant targeted therapy for early staged NSCLC. The second section focuses on targeted therapy in metastatic NSCLC. The list of targetable alteration now includes but is not limited to EGFR, ALK, ROS1, BRAF V600E, MET exon 14 skipping, RET, KRAS G12C, HER2 and NRG1. Potential drug resistance mechanisms and novel therapeutics under development are also discussed. The third section on immunotherapy in metastatic NSCLC, covers immunotherapy that are currently approved [anti-PD-(L)1 and anti-CTLA4], and agents that are under active research (e.g., anti-TIGIT, cancer vaccine, cellular therapy, cytokine and other TME modulating agents). This review encompasses the latest updates in targeted therapy and immunotherapy in lung cancer management and discusses the future direction in the field.

Redefining pleiotropic drug resistance in a pathogenic yeast: Pdr1 functions as a sensor of cellular stresses in Candida glabrata.

Candida glabrata is a prominent opportunistic fungal pathogen of humans. The increasing incidence of C. glabrata infections is attributed to both innate and acquired resistance to antifungals. Previous studies suggest the transcription factor Pdr1 and several target genes encoding ABC transporters are critical elements of pleiotropic defense against azoles and other antifungals. This study utilizes Hermes transposon insertion profiling to investigate Pdr1-independent and Pdr1-dependent mechanisms that alter susceptibility to the frontline antifungal fluconazole. Several new genes were found to alter fluconazole susceptibility independent of Pdr1 (CYB5, SSK1, SSK2, HOG1, TRP1). A bZIP transcription repressor of mitochondrial function (CIN5) positively regulated Pdr1 while hundreds of genes encoding mitochondrial proteins were confirmed as negative regulators of Pdr1. The antibiotic oligomycin activated Pdr1 and antagonized fluconazole efficacy likely by interfering with mitochondrial processes in C. glabrata. Unexpectedly, disruption of many 60S ribosomal proteins also activated Pdr1, thus mimicking the effects of the mRNA translation inhibitors. Cycloheximide failed to fully activate Pdr1 in a cycloheximide-resistant Rpl28-Q38E mutant. Similarly, fluconazole failed to fully activate Pdr1 in a strain expressing a low-affinity variant of Erg11. Fluconazole activated Pdr1 with very slow kinetics that correlated with the delayed onset of cellular stress. These findings are inconsistent with the idea that Pdr1 directly senses xenobiotics and support an alternative hypothesis where Pdr1 senses cellular stresses that arise only after engagement of xenobiotics with their targets. IMPORTANCE Candida glabrata is an opportunistic pathogenic yeast that causes discomfort and death. Its incidence has been increasing because of natural defenses to our common antifungal medications. This study explores the entire genome for impacts on resistance to fluconazole. We find several new and unexpected genes can impact susceptibility to fluconazole. Several antibiotics can also alter the efficacy of fluconazole. Most importantly, we find that Pdr1-a key determinant of fluconazole resistance-is not regulated directly through binding of fluconazole and instead is regulated indirectly by sensing the cellular stresses caused by fluconazole blockage of sterol biosynthesis. This new understanding of drug resistance mechanisms could improve the outcomes of current antifungals and accelerate the development of novel therapeutics.

Bedaquiline and clofazimine resistance in Mycobacterium tuberculosis: an in-vitro and in-silico data analysis

Bedaquiline is a core drug for the treatment of multidrug-resistant tuberculosis; however, the understanding of resistance mechanisms is poor, which is hampering rapid molecular diagnostics. Some bedaquiline-resistant mutants are also cross-resistant to clofazimine. To decipher bedaquiline and clofazimine resistance determinants, we combined experimental evolution, protein modelling, genome sequencing, and phenotypic data. For this in-vitro and in-silico data analysis, we used a novel in-vitro evolutionary model using subinhibitory drug concentrations to select bedaquiline-resistant and clofazimine-resistant mutants. We determined bedaquiline and clofazimine minimum inhibitory concentrations and did Illumina and PacBio sequencing to characterise selected mutants and establish a mutation catalogue. This catalogue also includes phenotypic and genotypic data of a global collection of more than 14 000 clinical Mycobacterium tuberculosis complex isolates, and publicly available data. We investigated variants implicated in bedaquiline resistance by protein modelling and dynamic simulations. We discerned 265 genomic variants implicated in bedaquiline resistance, with 250 (94%) variants affecting the transcriptional repressor (Rv0678) of the MmpS5-MmpL5 efflux system. We identified 40 new variants in vitro, and a new bedaquiline resistance mechanism caused by a large-scale genomic rearrangement. Additionally, we identified in vitro 15 (7%) of 208 mutations found in clinical bedaquiline-resistant isolates. From our in-vitro work, we detected 14 (16%) of 88 mutations so far identified as being associated with clofazimine resistance and also seen in clinically resistant strains, and catalogued 35 new mutations. Structural modelling of Rv0678 showed four major mechanisms of bedaquiline resistance: impaired DNA binding, reduction in protein stability, disruption of protein dimerisation, and alteration in affinity for its fatty acid ligand. Our findings advance the understanding of drug resistance mechanisms in M tuberculosis complex strains. We have established an extended mutation catalogue, comprising variants implicated in resistance and susceptibility to bedaquiline and clofazimine. Our data emphasise that genotypic testing can delineate clinical isolates with borderline phenotypes, which is essential for the design of effective treatments. Leibniz ScienceCampus Evolutionary Medicine of the Lung, Deutsche Forschungsgemeinschaft, Research Training Group 2501 TransEvo, Rhodes Trust, Stanford University Medical Scientist Training Program, National Institute for Health and Care Research Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Bill & Melinda Gates Foundation, Wellcome Trust, and Marie Skłodowska-Curie Actions.

Inferring density-dependent population dynamics mechanisms through rate disambiguation for logistic birth-death processes.

Density dependence is important in the ecology and evolution of microbial and cancer cells. Typically, we can only measure net growth rates, but the underlying density-dependent mechanisms that give rise to the observed dynamics can manifest in birth processes, death processes, or both. Therefore, we utilize the mean and variance of cell number fluctuations to separately identify birth and death rates from time series that follow stochastic birth-death processes with logistic growth. Our nonparametric method provides a novel perspective on stochastic parameter identifiability, which we validate by analyzing the accuracy in terms of the discretization bin size. We apply our method to the scenario where a homogeneous cell population goes through three stages: (1) grows naturally to its carrying capacity, (2) is treated with a drug that reduces its carrying capacity, and (3) overcomes the drug effect to restore its original carrying capacity. In each stage, we disambiguate whether the dynamics occur through the birth process, death process, or some combination of the two, which contributes to understanding drug resistance mechanisms. In the case of limited sample sizes, we provide an alternative method based on maximum likelihood and solve a constrained nonlinear optimization problem to identify the most likely density dependence parameter for a given cell number time series. Our methods can be applied to other biological systems at different scales to disambiguate density-dependent mechanisms underlying the same net growth rate.

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.

Abstract 6009: Developing drug-induced resistant tumor models for efficacy evaluation of next-generation anticancer therapies

Abstract The therapeutic landscape of cancer has been transformed over the last few decades. Our understanding of cancer and its therapeutic approach has improved greatly due to advanced cancer biology, functional imaging and next-generation sequencing. One of the key challenges in cancer therapy is how to effectively kill cancer cells while leaving normal cells intact. As specific oncogenic drivers have been successfully identified, targeted treatments have achieved great success in clinical practice. However, acquired drug resistance remains the major barrier to sustained success of targeted cancer therapy. Those patients who initially respond well to targeted therapies eventually become resistant to the treatments. Uncovering the underlying mechanism would help develop novel therapies that overcome the drug resistance.To mimic the clinical resistance after long-term drug treatment, we established a panel of drug-induced resistant tumor models by continuous dosing of targeted drugs to tumor-bearing mice or cancer cell lines, covering a series of first-line targeted drugs including Sotorasib, Palbociclib, Ibrutinib, Capmatinib, Fulvestrant, Tamoxifen and TDM-1. Resistant models were derived from sensitive ones harboring specific oncogenic drivers. After treated with targeted drugs and passaged several times, resistant models exhibited stable resistance phenotype. Given that target gene mutation, alternative pathway activation or tumor microenvironment evolution could promote therapy resistance and cancer progression, we performed transcript and protein analysis to explore the molecular mechanism, and evaluated the potential therapeutic strategies overcoming drug resistance in the established models. Taken together, drug-induced resistant tumor models provide a promising opportunity to the better understanding of drug resistance mechanisms and to the accelerated development of next-generation anticancer agents. Citation Format: Ting Ni, Gaoxiang Liu, Tongxin Huo, Wenting Shi, Qingyang Gu, Qunsheng Ji. Developing drug-induced resistant tumor models for efficacy evaluation of next-generation anticancer therapies [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 6009.

Computational Methods for the Analysis and Prediction of EGFR-Mutated Lung Cancer Drug Resistance: Recent Advances in Drug Design, Challenges and Future Prospects.

Lung cancer is a major cause of cancer deaths worldwide, and has a very low survival rate. Non-small cell lung cancer (NSCLC) is the largest subset of lung cancers, which accounts for about 85% of all cases. It has been well established that a mutation in the epidermal growth factor receptor (EGFR) can lead to lung cancer. EGFR Tyrosine Kinase Inhibitors (TKIs) are developed to target the kinase domain of EGFR. These TKIs produce promising results at the initial stage of therapy, but the efficacy becomes limited due to the development of drug resistance. In this paper, we provide a comprehensive overview of computational methods, for understanding drug resistance mechanisms. The important EGFR mutants and the different generations of EGFR-TKIs, with the survival and response rates are discussed. Next, we evaluate the role of important EGFR parameters in drug resistance mechanism, including structural dynamics, hydrogen bonds, stability, dimerization, binding free energies, and signaling pathways. Personalized drug resistance prediction models, drug response curve, drug synergy, and other data-driven methods are also discussed. Recent advancements in deep learning; such as AlphaFold2, deep generative models, big data analytics, and the applications of statistics and permutation are also highlighted. We explore limitations in the current methodologies, and discuss strategies to overcome them. We believe this review will serve as a reference for researchers; to apply computational techniques for precision medicine, analyzing structures of protein-drug complexes, drug discovery, and understanding the drug response and resistance mechanisms in lung cancer patients.

The role of resveratrol, Sirtuin1 and RXRα as prognostic markers in ovarian cancer

ObjectiveOvarian cancer is the most lethal gynecologic cancer. Resveratrol (RSV) is known to alter metabolism in cancer. It affects the nuclear retinoid-X-receptor (RXR), which implies a modulating effect of RXR to gynaecologic cancers. Furthermore, RSV targets Sirtuin1 (Sirt1), a histone deacetylase.Study design123 tissue samples of patients with serous or mucinous ovarian cancer were examined for expression of Sirt1 and RXR. Ovarian cell lines were treated with RSV and consequences on viability and apoptosis were evaluated. The influence of RSV to Sirt1 and RXR expression was analyzed by western blottingResultsA correlation of nuclear Sirt1 and RXRα expression could be detected (p = 0.006). Co-expression of nuclear RXRα and cytoplasmic (p = 0.026) or nuclear (p = 0.041) Sirt1 was associated with significantly increased overall survival in advanced tumour stages. Viability was decreased in all cell lines after stimulation with resveratrol, while cell apoptosis was increased. RSV treatment led to significant lower Sirt1 expression in A2780 cells (p = 0.025) and significant increased RXR expression in cisA2780 cells (p = 0.012)ConclusionIn order to use RSV as medical target, studies could be developed to improve the understanding of drug resistance mechanisms and consequently improve treatment outcome.

Phosphoproteomic Analysis of Primary Myeloma Patient Samples Identifies Distinct Phosphorylation Signatures Correlating with Chemo-Sensitivity Profiles in an Ex Vivo Drug Sensitivity Testing Platform

Introduction: Multiple myeloma (MM) is characterized by the clonal expansion of plasma cells in the bone marrow resulting in end-organ damage. Despite an extensive increase in the five-year survival rate in recent years, MM is still considered an incurable disease as patients will repeatedly relapse and develop resistance to current chemotherapies. A key focus for the personalization of myeloma therapy is understanding the biological mechanisms of drug resistance and identifying clinically useful biomarkers of therapeutic response. Highly efficient techniques for the enrichment of phosphorylated peptides followed by high resolution mass spectrometry facilitates the quantitation of thousands of site-specific phosphorylation events. Here, we have performed a phosphoproteomic analysis on MM cell lysates stratified based on their ex vivo drug response profiles to advance our understanding of drug resistance mechanisms.Materials and Methods: CD138 + plasma cells were isolated from 20 adult MM patient bone marrow aspirates at diagnosis (n=7) or relapse (n=13). Samples were grouped based on ex vivo drug sensitivity and resistance testing (DSRT) as follows: highly sensitive (Group I), sensitive (Group II), resistant (Group III), highly resistant (Group IV) [1]. For the phosphoproteomic analysis, peptides were generated and purified using the filter aided sample preparation (FASP) protocol. Peptide tandem mass tag (TMT) labelling, Fe 3+ immobilized metal ion affinity chromatography (IMAC), synchronous precursor selection (SPS), and triple stage tandem mass spectrometry (MS3) was performed. Nonenriched peptides were used for proteomic analysis. Resulting data was analysed using MaxQuant, followed by normalization of phosphosite intensities using the internal reference scale (IRS) method, and statistical analysis using Perseus. Functional enrichment and kinase enrichment analyses were performed on significant phosphoproteins using g:profiler and KEA2, respectively.Results: Our quantitative MS-based phosphoproteomic analysis identified 2,945 phosphorylation sites on 2,232 phosphopeptides from 690 phosphoproteins. Of these phosphorylation sites, 176 were significantly changed between all four DSRT groups and 267 were significantly changed between Group I and Group IV (False Discovery Rate (FDR) < 0.05). Hierarchical clustering was performed to highlight the distinct phosphoproteomic profiles associated with each DSRT group, of which the very sensitive (Group I) and very resistant (Group IV) subgroups demonstrated a well-defined separation (Fig. 1A, 1B). KEGG pathway analysis and gene ontology (GO) analysis of significantly increased phosphorylated proteins in Group IV compared to Group I MM patients demonstrated an increased phosphorylation of proteins associated with tight junctions, the Rap1 signalling pathway and the phosphatidylinositol signalling system; indicating an upregulation of cell adhesion associated processes in drug resistant MM. Phosphoproteins increased in abundance in Group I compared to Group IV MM patients revealed an increased phosphorylation of proteins involved in translation and RNA processing including the spliceosome, RNA transport and RNA binding pathways (Fig. 1C). We identified filamin A serine 2152, RAS guanyl-releasing protein 2 serine 576 and proto-oncogene tyrosine-protein kinase Src serine 17 as increased in Group IV MM, and nuclease-sensitive element-binding protein 1 (YBX1) serine 165, CD44 serine 697 and Bcl2-associated agonist of cell death (BAD) serine 99 as increased in Group I MM. KEA of the upregulated phosphoproteome in Group IV revealed an enrichment of cyclin dependent kinase 1 (CDK1) and ribosomal s6 kinases (RPS6K) whereas casein kinase 2 (CK2) and the glycolysis-associated kinases were enriched in Group I (Fig. 1D).Conclusion: Our study has generated a phosphoproteomic dataset demonstrating distinct phosphorylation signatures associated with drug sensitivity in clinical MM plasma cells. The identification of phosphorylation events associated with drug resistance provides a basis for further exploration of these events and associated signalling pathways to further understand drug resistance mechanisms in MM and identify potential biomarkers of therapeutic response and targets for drug re-sensitization in MM.

N-Glycoproteomics Study of Putative N-Glycoprotein Biomarkers of Drug Resistance in MCF-7/ADR Cells.

The online version contains supplementary material available at 10.1007/s43657-021-00029-8.

Preliminary Study to Obtain Insights on the Proteomic Profile of Filipino Non-Small Cell Lung Carcinoma (NSCLC)

NSCLC remains to be the leading cause of cancer incidence and mortality in the Philippines. Early diagnosis, a better understanding of drug resistance mechanisms, and proper treatment monitoring are necessary to lower the incidence and mortality rate of NSCLC. As a proof of concept to investigate the proteomic profile of Filipino NSCLC, this study performed quantitative proteomic analysis to identify aberrant expressions in the tumor tissue relative to the adjacent normal tissue specimen of one Filipino NSCLC patient. A total of 4518 proteins were identified and from this, 1855 proteins were found to be significantly differentially expressed. Functional and pathway analyses were done to the 860 upregulated and downregulated proteins with at least four-fold expression change. The analysis revealed the possible activation of the upregulated protein MUC1, a known oncogenic driver involved in the stimulation of pathways that promote angiogenesis in NSCLC tumors and prevent apoptosis. Signal transducers and activators of transcription (STAT1 and STAT3), also found upregulated in the tumor specimen, are known to interact with MUC1, which results in the expression of proteins for cell proliferation. The analysis also suggests the stabilization of HIF, which may allow cell growth in the hypoxic tumor environment and aid in metabolic adaptation in tumor cells. The results also suggest the activation of EIF2 signaling that may lead to continuous translation of oncogenic proteins. Our data demonstrate the rich proteomic information that can be obtained from profiling of the NSCLC proteome and applications for a better understanding of NSCLC tumorigenicity. Further study should be performed on a larger cohort of Filipino NSCLC patients to provide the proteomic profile of Filipino NSCLC and extract information for biomarker and drug discovery. Data are available via ProteomeXchange with identifier PXD027710.

MgrB Inactivation Confers Trimethoprim Resistance in Escherichia coli.

After several decades of use, trimethoprim (TMP) remains one of the key access antimicrobial drugs listed by the World Health Organization. To circumvent the problem of trimethoprim resistance worldwide, a better understanding of drug-resistance mechanisms is required. In this study, we screened the single-gene knockout library of Escherichia coli, and identified mgrB and other several genes involved in trimethoprim resistance. Subsequent comparative transcriptional analysis between ΔmgrB and the wild-type strain showed that expression levels of phoP, phoQ, and folA were significantly upregulated in ΔmgrB. Further deleting phoP or phoQ could partially restore trimethoprim sensitivity to ΔmgrB, and co-overexpression of phoP/Q caused TMP resistance, suggesting the involvement of PhoP/Q in trimethoprim resistance. Correspondingly, MgrB and PhoP were shown to be able to modulated folA expression in vivo. After that, efforts were made to test if PhoP could directly modulate the expression of folA. Though phosphorylated PhoP could bind to the promotor region of folA in vitro, the former only provided a weak protection on the latter as shown by the DNA footprinting assay. In addition, deleting the deduced PhoP box in ΔmgrB could only slightly reverse the TMP resistance phenotype, suggesting that it is less likely for PhoP to directly modulate the transcription of folA. Taken together, our data suggested that, in E. coli, MgrB affects susceptibility to trimethoprim by modulating the expression of folA with the involvement of PhoP/Q. This work broadens our understanding of the regulation of folate metabolism and the mechanisms of TMP resistance in bacteria.

Thinking Differently about Cancer Treatment Regimens.

Most experimental cancer drugs ultimately fail during the course of clinical development, contributing to the high cost of the few that are granted regulatory approval. Moreover, approved drugs often deliver only modest clinical benefit to patients with advanced disease due to the development of resistance. Here, we discuss opportunities we consider promising to overcome drug resistance associated with interactions between signaling pathways and the presence of multiple coexisting cell states within tumors with distinct vulnerabilities. We highlight how understanding drug-resistance mechanisms can enable innovative treatment regimens that deliver longer-lasting benefit to patients.