Biomarkers Of Drug Resistance Research Articles

Long noncoding RNAs: A novel insight in the leukemogenesis and drug resistance in acute myeloid leukemia.

Acute myeloid leukemia (AML) is a common hematological disorder with heterogeneous nature that resulted from blocked myeloid differentiation and an enhanced number of immature myeloid progenitors. During several decades, different factors, including cytogenetic, genetic, and epigenetic have been reported to contribute to the pathogenesis of AML by inhibiting the differentiation and ensuring the proliferation of myeloid blast cells. Recently, long noncoding RNAs (lncRNAs) have been considered as potential diagnostic, therapeutic, and prognostic factors in different human malignancies including AML. Altered expression of lncRNAs is correlated with the transformation of hematopoietic stem and progenitor cells into leukemic blast cells because of their distinct role in the key cellular processes. We discuss the significant role of lncRNAs in the proliferation, survival, differentiation, leukemic stem cells in AML and their involvement in different molecular pathways (insulin-like growth factor type I receptor, FLT3, c-KIT, Wnt, phosphatidylinositol 3-kinase/protein kinase-B, microRNAs), and associated mechanisms such as autophagy, apoptosis, and glucose metabolism. In addition, we aim to highlight the role of lncRNAs as reliable biomarkers for diagnosis, prognosis, and drug resistance for precision medicine in AML.

Up-regulation of GSTT1 in serous ovarian cancer associated with resistance to TAXOL / carboplatin

Serous ovarian cancer (SOC) is the most common women cancer and the leading cause of cancer-related mortality among the gynaecological malignancies. Although effective chemotherapeutics combined with surgery are developed for the treatment, the five-year survival rate is unsatisfactory due to chemoresistance. To overcome this shortcoming of chemotherapy, we established taxol and carboplatin resistant SOC cell lines for the understandings of the molecular and cellular mechanisms of chemoresistance. Here, we found that these chemoresistant cell lines showed less viability and proliferation, due to more cells arrested at G0/G1 phase. Glutathione-S-transferases-theta1 (GSTT1) was significantly upregulated in these chemoresistant cells, along with other chemoresistant genes. Meanwhile, GSTT1 expression was also significantly upregulated in the SOC patient tissues after taxol treatment, indicating this upregulation was physiologically relevant to chemotherapy. Further, suppression of GSTT1 expression by shRNA in SOC cell lines led to more sensitivity to drug treatment, through increasing divided cells and promoting cell death. Moreover, the expression of DNA topoisomerase 1 (Topo I) was in synergy with that of GSTT1 in the chemoresistant cells, and GSTT1 can bind to Topo I in vitro, which suggested GSTT1 could function through DNA repair mechanism during chemoresistance. In summary, our data imply that GSTT1 may be a potential biomarker or indicator of drug resistance in serous ovarian cancer.

HOX gene regulation in glioma stem cells, mediators of resistance in breast cancer, and paradoxical therapeutic interventions

Therapy resistance remains a major challenge during the treatment of patients with advanced cancer. Due to the complex nature of the cellular and molecular mechanisms underlying therapy resistance, research efforts to tackle this challenge have focused on diverse aspects: from cancer stem cell (CSC) biology, therapy resistance-specific signatures to the development of new combinatorial therapeutic approaches. Among other articles, the August issue of Molecular Oncology includes several studies that directly or indirectly explore therapy resistance in patients with advanced cancer. In some cancers, therapeutic resistance has been linked to the presence of CSCs. In glioma, for example, glioma stem cells (GSCs) represent a tumor cell subpopulation underlying tumor relapse. Understanding the molecular mechanisms behind GSC gene expression may give new insights on tumorigenesis and tumor relapse. In their recent study, Le Boiteux et al. [[1]] analyzed six patient-derived GSC lines, as well as 70 primary adult diffuse glioma samples to map the mechanisms leading to deregulation of the HOX gene clusters, which have been previously implicated in the oncogenic potential of GSCs. The authors identified widespread reactivation of HOX genes in adult IDH wild-type (IDHwt) diffuse glioma samples and GSCs. HOX gene deregulation was associated with self- and cross-regulatory interactions between HOX transcription factors, but not with genomic rearrangements. Integrative analysis of high-throughput DNA methylation analysis, ChIPseq, and RNAseq data demonstrated that the absence of hypermethylation on canonical and alternative bivalent CpG islands in promoters, as well as loss of the H3K27me3 epigenetic mark, underlies aberrant gene expression of HOX clusters in IDHwt gliomas. Besides providing a comprehensive epigenetic analysis of HOX gene regulation in glioma, the study by Le Boiteux et al. highlights the complexity of HOX gene expression via alternative promoters in cancer. In a different setting, Mohammad Sultan and colleagues employed an in vivo genome-wide shRNA screen to identify potential mediators or biomarkers of paclitaxel resistance in patients with advanced breast cancer [[2]]. The transcriptional repressor BCL6 was identified among the top paclitaxel resistance hits, and BCL6 overexpression was detected in tumors of chemotherapy-resistant patients. To further test the role of BCL6 in paclitaxel resistance, the authors performed BCL6 knockdown and BCL6 inhibitor experiments both in vitro and in vivo, in a mouse model of triple-negative breast cancer. BCL6 targeting in preclinical models enhanced the efficacy of paclitaxel treatment. Thus, BCL6 may serve as a biomarker for drug resistance and may potentially be targeted for the treatment of patients with breast cancer that have developed paclitaxel resistance. In addition to chemotherapy, targeted therapies designed to block mitogenic signaling pathways are often used for the treatment of patients with cancer. However, drug resistance to these therapeutic agents represents a major challenge for the treatment of advanced cancer. In their perspective, Matheus Henrique Dias and Rene Bernards explore the prospects of a ‘paradoxical intervention’ strategy for the treatment of therapy-resistant cancers [[3]]. Such a strategy would involve overactivation, rather than inhibition, of mitotic signaling in cancer cells. In their view, such an approach would result in an overload of the stress response pathways and disruption of cancer cell homeostasis and viability. The authors review related data from several independent experimental models, discuss future perspectives, and explore the potential drawbacks of such a paradoxical intervention strategy for the treatment of patients with cancer.

Abstract 2381: miRNome exosomal characterization reveals a distinct signature able to predict cisplatin-response in NSCLC patients

Abstract Background: Non-small cell lung cancer (NSCLC) is one leading cause of death worldwide, with a 5-year survival rate of only 24%. Late diagnosis and the innate or acquired anti-cancer drug resistance are the main causes of this high mortality. In recent years, targeted drugs and immunotherapies have substantially increased the survival in aprox 15% of patients. However, the vast majority continue to receive the standard platinum-based chemotherapy (CDDP), although they present poor response to the treatment. Therefore, it is extremely important to identify new biomarkers for survival, prognosis and drug-resistance in NSCLC. Liquid biopsy represents a source of potentially actionable biomarkers, being minimally invasive and allowing to track tumor heterogeneity and detecting very early emergence of therapy resistance and recurrence. Among them, exosomal miRNAs are highly implicated in cancer progression and have great biomedical relevance due to their stability, feasible detection and their functional capacity to regulate gene expression. Methods: To study the implication of exosomal miRNAs in the induction of CDDP resistance, we analyzed the exosomal content of 3 paired CDDP sensitive and resistant lung cancer (H23S/R), and ovarian cancer (A2780S/R and 41M/R) cell lines by small RNAseq and we compared the profiles of the two phenotypes looking for candidates over-represented in the resistant cells-exosomes. Then, we performed a qRT-PCR validation of the candidates and studied their implication in the development of CDDP-resistance through its overexpression in our cell models and subsequent exposure to CDDP. Finally, we evaluated the clinical relevance of the validated candidates in lung, studying their expression levels in a prospective cohort of 51 advanced NSCLC patients and 10 healthy controls with a 3 years follow-up. Results: We identified 2 known miRNAs (miR1 miR2) and 1 novel miRNA (miR3) that were overexpressed in the exosomes of the resistant subtypes and validated in the lung cancer cell line H23. Among them, miR1 overexpression led to an increased sensitivity to CDDP in the H23 R phenotype. This could mean that resistant cancer cells are eliminating miR1 through exosomes to become more aggressive. Regarding exosomal miRNA expression in patients, the only miRNA that was differentially elevated in NSCLC patients vs controls was miR3, showing that it could be involved in the establishment of NSCLC. Then, we divided NSCLC patients in high and low miRNA expression levels, finding that bearing high levels of exosomal miR1 and miR2 extremely increased the risk of recurrence and death in NSCLC patients. Conclusions: We demonstrated that exosomal levels of miR1 and 2 would allow monitoring the prognosis and response to platinum in patients with advanced NSCLC, facilitating the choice of alternative therapies; and that miR3 in liquid biopsy could be useful as a biomarker for early diagnosis. Citation Format: Miranda Burdiel, Julia Jimenez, Carlos Rodriguez-Antolin, Olga Pernia, Rocio Rosas, Dario Sanchez-Cabrero, Patricia Cruz, Itsaso Losantos, Javier de Castro, Inmaculada Ibanez de Caceres. miRNome exosomal characterization reveals a distinct signature able to predict cisplatin-response in NSCLC patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2381.

New Studies Reveal Potential Mechanisms of Resistance to CDK4/6 Inhibitors in HR+/HER2- Breast Cancer.

Research focused on barriers to the real-world use of CDK4/6 inhibitor therapy in patients with HR+/HER2– breast cancer reveals potential mechanisms and biomarkers of drug resistance.

Screening of metabolites in the treatment of liver cancer xenografts HepG2/ADR by psoralen-loaded lipid nanoparticles

ObjectiveOur study aimed to find potential biomarkers for drug resistance in liver cancer cells using metabolomics and further to evaluate the potential of psoralen-loaded polymer lipid nanoparticles (PSO-PLNs) to reverse the resistance of cells to doxorubicin. MethodsWe used LC-MS-based non-targeted metabolomics, also known as global metabolite profiling, to screen in serum and urine of mice engrafted with a liver cancer cell line sensitive (HepG2/S) or resistant to doxorubicin (HepG2/ADR) for differentially regulated metabolites. We subsequently quantified the abundance of these metabolites in serum and the urine of mice. The mice were engrafted with HepG2 cells resistant against doxorubicin and were treated with I) doxorubicin, II) a combination of doxorubicin and psoralen and III) a combination of doxorubicin and psoralen packed in polymer lipid nanoparticles. ResultsMetabolites found to be differentially present in urine of mice engrafted with resistant HepG2 cells were: hippuric acid, hyaluronic acid, pantothenic acid, and betaine; retinoic acid and α-linolenic acid were found to be reduced in serum samples of mice with HepG2 cells resistant to doxorubicin. The targeted analysis showed that the degree of regression of metabolic markers in groups differed: treatment group 2 had stronger degree of regression than treatment group 1 and the negative control group had the smallest, which indicates that the PSO-PLNs have superior properties compared with other treatments. ConclusionPsoralen reverses drug resistance of liver cancer cells and its efficacy can be increased by encapsulation in polymer lipid nanoparticles.

Relationship between long non-coding RNA PCAT-1 expression and gefitinib resistance in non-small-cell lung cancer cells

BackgroundGefitinib, an epidermal growth factor receptor tyrosine kinase inhibitor, has been used as first-line treatment for advanced non-small-cell lung cancer (NSCLC). However, during treatment, cancer cells often develop resistance to gefitinib, the mechanisms of which are not fully understood. This study was designed to elucidate the expression and role of long non-coding RNA (lncRNA)-PCAT-1, a potential biomarker for drug resistance and a therapeutic target for NSCLC, in gefitinib resistance in NSCLC cells.MethodsIn this study, we verified differential PCAT-1 expression in NSCLC gefitinib-resistant tissues or cells. PCAT-1 knockdown, clone formation, Transwell, flow cytometry, and immunofluorescence assays were used to verify the correlation between PCAT-1 and gefitinib sensitivity. A nude mouse tumor-bearing model verified that PCAT-1 can reverse gefitinib resistance in vivo. Then, a PI3K/Akt agonist was used to verify the possible mechanism of PCAT-1 action.ResultsPCAT-1 is highly expressed in gefitinib-resistant NSCLC tissues and cells. PCAT-1 knockdown enhanced gefitinib sensitivity and gefitinib-induced apoptosis in H1299/GR cells. PCAT-1 knockdown reduced tumor volume and weight, and reversed acquired gefitinib resistance in vivo. PCAT-1 knockdown inhibited AKT and GSK3 phosphorylation in H1299/GR cells. A PI3K/AKT agonist reversed PCAT-1 knockdown-mediated enhancement of gefitinib sensitivity in H1299/GR cellsConclusionPCAT-1 knockdown improves sensitivity to gefitinib by inhibition of AKT and GSK3 phosphorylation in NSCLC. PCAT-1 is as potential target for improving the clinical efficacy of gefitinib.

Extracellular vesicles and leishmaniasis: Current knowledge and promising avenues for future development

Extracellular vesicles (EVs) are small, membrane-bound “delivery trucks” that are present in the extracellular environment, including biological fluids. EVs are capable of inducing changes in the physiological status of neighboring cells through the transfer of key macromolecules, and are thought to play a role in a number of pathological processes. Leishmaniasis, caused by the protozoan parasite Leishmania, is an important example. The biology of Leishmania EVs has been studied in detail, and findings point to their role in exacerbation of disease and potential involvement in the perpetuation of drug resistance. Furthermore, the use of EVs for development of vaccines has been explored, as well as their potential use in a number of fields as biomarkers of disease and drug resistance. Here we discuss the latest findings on EVs, with a particular focus on Leishmania, as well as potential avenues for their future development and clinical applications.

A cell-to-patient machine learning transfer approach uncovers novel basal-like breast cancer prognostic markers amongst alternative splice variants

BackgroundBreast cancer is amongst the 10 first causes of death in women worldwide. Around 20% of patients are misdiagnosed leading to early metastasis, resistance to treatment and relapse. Many clinical and gene expression profiles have been successfully used to classify breast tumours into 5 major types with different prognosis and sensitivity to specific treatments. Unfortunately, these profiles have failed to subclassify breast tumours into more subtypes to improve diagnostics and survival rate. Alternative splicing is emerging as a new source of highly specific biomarkers to classify tumours in different grades. Taking advantage of extensive public transcriptomics datasets in breast cancer cell lines (CCLE) and breast cancer tumours (TCGA), we have addressed the capacity of alternative splice variants to subclassify highly aggressive breast cancers.ResultsTranscriptomics analysis of alternative splicing events between luminal, basal A and basal B breast cancer cell lines identified a unique splicing signature for a subtype of tumours, the basal B, whose classification is not in use in the clinic yet. Basal B cell lines, in contrast with luminal and basal A, are highly metastatic and express epithelial-to-mesenchymal (EMT) markers, which are hallmarks of cell invasion and resistance to drugs. By developing a semi-supervised machine learning approach, we transferred the molecular knowledge gained from these cell lines into patients to subclassify basal-like triple negative tumours into basal A- and basal B-like categories. Changes in splicing of 25 alternative exons, intimately related to EMT and cell invasion such as ENAH, CD44 and CTNND1, were sufficient to identify the basal-like patients with the worst prognosis. Moreover, patients expressing this basal B-specific splicing signature also expressed newly identified biomarkers of metastasis-initiating cells, like CD36, supporting a more invasive phenotype for this basal B-like breast cancer subtype.ConclusionsUsing a novel machine learning approach, we have identified an EMT-related splicing signature capable of subclassifying the most aggressive type of breast cancer, which are basal-like triple negative tumours. This proof-of-concept demonstrates that the biological knowledge acquired from cell lines can be transferred to patients data for further clinical investigation. More studies, particularly in 3D culture and organoids, will increase the accuracy of this transfer of knowledge, which will open new perspectives into the development of novel therapeutic strategies and the further identification of specific biomarkers for drug resistance and cancer relapse.

Recent Discoveries of Macromolecule- and Cell-Based Biomarkers and Therapeutic Implications in Breast Cancer

Breast cancer is the most commonly diagnosed cancer type and the leading cause of cancer-related mortality in women worldwide. Breast cancer is fairly heterogeneous and reveals six molecular subtypes: luminal A, luminal B, HER2+, basal-like subtype (ER−, PR−, and HER2−), normal breast-like, and claudin-low. Breast cancer screening and early diagnosis play critical roles in improving therapeutic outcomes and prognosis. Mammography is currently the main commercially available detection method for breast cancer; however, it has numerous limitations. Therefore, reliable noninvasive diagnostic and prognostic biomarkers are required. Biomarkers used in cancer range from macromolecules, such as DNA, RNA, and proteins, to whole cells. Biomarkers for cancer risk, diagnosis, proliferation, metastasis, drug resistance, and prognosis have been identified in breast cancer. In addition, there is currently a greater demand for personalized or precise treatments; moreover, the identification of novel biomarkers to further the development of new drugs is urgently needed. In this review, we summarize and focus on the recent discoveries of promising macromolecules and cell-based biomarkers for the diagnosis and prognosis of breast cancer and provide implications for therapeutic strategies.

Molecular Landscape of Tp53 Mutations in Breast Cancer and Their Utility for Predicting Response to HER-Targeted Therapy in HER2 Amplification-Positive and HER2 Mutation-Positive Amplification-Negative Patients

Purpose: To determine the mutation rate of p53 in breast cancer and the predictive value for anti-HER2 treatment by ctDNA detection. Patients and Methods: The Tp53 mutation features were analyzed in Geneplus cohort (n=1,184). The MSK-BREAST cohort was used to explore the value of Tp53 for predicting the efficacy of anti-HER-2 antibody drugs. Then, next-generation sequencing was performed on ctDNA in phase Ib, phase Ic, phase II clinical trials of pyrotinib (HER2-amplification patients) and an investigator-initiated phase-II study of pyrotinib (HER2-mutant amplification-negative patients) to analyze the value of Tp53 for predicting the efficacy of HER2 TKIs. The MSK-BREAST cohort, MutHER cohort and SUMMIT cohort were used to verify our findings. Results: Tp53 mutations were detected in 53.1% (629/1,184) of patients in the Geneplus cohort. Tumors with Tp53 mutation showed a shorter PFS for anti-HER2 antibody treatment. However, no difference in PFS was shown for HER2 amplification-positive patients with different Tp53 statuses in the combination analysis of the pyrotinib phase Ib, phase Ic, and phase II clinical trials or the MSK-BREAST cohort. In patients with HER2 mutation and amplification negativity, Tp53 mutation-positive patients showed a trend for worse prognosis for anti-HER2 TKIs treatment than Tp53-wild-type patients in our investigator-initiated phase II study, and this trend was confirmed in the combined analysis of MutHER and SUMMIT cohorts. Conclusions: Tp53 gene mutation analysis can be used to identify biomarkers of anti-HER2 antibody drug resistance in HER2 amplification-positive patients and HER2 TKI resistance in HER2 mutation-positive and amplification-negative patients. Funding Statement: The present study was supported by the National Natural Science Foundation of China (No. 81874122) and Chinese Academy of Medical Sciences (CAMS) Initiative for Innovative Medicine (2017-I2M-3-004) Declaration of Interests: The authors declare that there are no competing interests. Ethics Approval Statement: All the studies were conducted in accordance with the Declaration of Helsinki and the principles of Good Clinical Practice and were approved by the Regulatory and Ethics Committees of National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College. All participants provided written informed consent.

Surrogate endpoints for early-stage breast cancer: a review of the state of the art, controversies, and future prospects.

Drug approval for early-stage breast cancer (EBC) has been historically granted in the context of registration trials based on adequate outcomes such as disease-free survival and overall survival. Improvements in long-term outcomes have made it more difficult to demonstrate the clinical benefit of a new cancer drug in large, randomized, comparative clinical trials. Therefore, the use of surrogate endpoints rather than traditional measures allows for cancer drug trials to proceed with smaller sample sizes and shorter follow-up periods, which reduces drug development time. Among surrogate endpoints for breast cancer, the increase in pathological complete response (pCR) rates was considered appropriate for accelerated drug approval. The association between pCR and long-term outcomes was strongest in patients with aggressive tumor subtypes, such as triple-negative and human epidermal growth factor receptor 2 (HER2)-positive/hormone receptor-negative breast cancers. Whereas in hormone receptor-positive/HER2-negative EBC, the most accepted surrogate markers for endocrine therapy–based trials include changes in Ki67 and the preoperative endocrine prognostic index. Beyond the classic endpoints, further prognostic tools are required to provide EBC patients with individualized and effective therapies, and the neoadjuvant setting provides an excellent platform for drug development and biomarker discovery. Nowadays, the availability of multigene signatures is offering a standardized quantitative and reproducible tool to potentiate the efficacy of standard treatment for high-risk patients and develop de-escalated treatments for patients at lower risk of relapse. In this article, we first evaluate the surrogacies used for long-term outcomes and the underlying evidence supporting the use of each surrogate endpoint for the accelerated or regular drug approval process in EBC. Next, we provide an overview of the most recent studies and innovative strategies in a (neo)adjuvant setting as a platform to accelerate new drug approval. Finally, we highlight some clinical trials aimed at tailoring systemic treatment of EBC using prognosis-related factors or early biomarkers of drug sensitivity or resistance.

Pygo2 as a novel biomarker in gastric cancer for monitoring drug resistance by upregulating MDR1.

Chemotherapy is the main therapy for gastric cancer (GC) both before and after surgery, but the emergence of multidrug resistance (MDR) often leads to disease progression and recurrence. P-glycoprotein, encoded by MDR1, is a well-known multidrug efflux transporter involved in drug resistance development. Pygo2 overexpression has been identified in several cancers. Previous studies have shown that abnormal expression of Pygo2 is related to tumorigenesis, chemoresistance, and tumor progression. In this study, to evaluate the underlying relationship between Pygo2 and MDR1 in GC, we constructed GC drug-resistant cell lines, SGC7901/cis-platinum (DDP), and collected tissue from GC patients' pre-and post-chemotherapy. We found that Pygo2 was overexpressed in GC, especially in GC drug-resistant cell lines and GC patients who underwent neoadjuvant DDP-based chemotherapy. Pygo2 overexpression may precede MDR1 and correlates with MDR1 in GC patients. Furthermore, knock-down of Pygo2 induced downregulation of MDR1 and restored SGC7901/DDP's sensitivity to DDP. Further mechanistic analysis demonstrated that Pygo2 could modulate MDR1 transcription by binding to the MDR1 promoter region and promoting MDR1 activation. The overall findings reveal that Pygo2 may be a promising biomarker for monitoring drug resistance in GC by regulating MDR1.

The novel potential multidrug-resistance biomarkers for Pseudomonas aeruginosa lung infections using transcriptomics data analysis

Abstract Development of multidrug resistance is the main obstacle for treating infections of Pseudomonas aeruginosa, an opportunistic pathogen responsible for a wide range of persistent infections throughout the body. Hence, identifying the major genes contributing to the development of multidrug resistance in Pseudomonas aeruginosa could help to introduce new efficient drugs to prevent resistance development. Here we conducted a differential gene expression analysis and a series of systems biology investigations on a RNASeq data set of multidrug resistant Pseudomonas aeruginosa isolates obtained from the patients’ airways and wild-type, drug-sensitive strains. Respectively 67 and 178 up- and down-regulated genes were detected, including several genes of unknown functions that their functional characterization will help to elucidate the hidden mechanisms for multidrug resistance development in Pseudomonas aeruginosa. By inspecting the constructed gene regulatory network, two cases of feed forward loops were identified which in the case of establishing the type of regulatory interactions between transcription factors and their target genes, as activatory or inhibitory, their true contribution to multidrug resistance will be better understood. Inspecting the constructed gene co-expression network revealed co-expression between four deregulated genes including PA14_32830, PA14_03380, fpvA and PA14_15610 and four already known drug resistance biomarkers. Functional characterization of these four co-expressed genes, will elucidate their possible roles in the process of multidrug resistance development in Pseudomonas aeruginosa. These findings will suggest new potential multidrug resistance biomarkers that following confirmation by larger number of samples, can be considered as new promising drug targets.

Metabolic profiles of multidrug resistant and extensively drug resistant Mycobacterium tuberculosis unveiled by metabolomics

Although treatable with antibiotics, tuberculosis is a leading cause of death. Mycobacterium tuberculosis antibiotic resistance is becoming increasingly common and disease control is challenging. Conventional drug susceptibility testing takes weeks to produce results, and treatment is often initiated empirically. Therefore, new methods to determine drug susceptibility profiles are urgent. Here, we used mass-spectrometry-based metabolomics to characterize the metabolic landscape of drug-susceptible (DS), multidrug-resistant (MDR) and extensively drug-resistant (XDR) M. tuberculosis. Direct infusion mass spectrometry data showed that DS, MDR, and XDR strains have distinct metabolic profiles, which can be used to predict drug susceptibility and resistance. This was later confirmed by Ultra-High-Performance Liquid Chromatography and High-Resolution Mass Spectrometry, where we found that levels of ions presumptively identified as isoleucine, proline, hercynine, betaine, and pantothenic acid varied significantly between strains with different drug susceptibility profiles. We then confirmed the identification of proline and isoleucine and determined their absolute concentrations in bacterial extracts, and found significantly higher levels of these amino acids in DS strains, as compared to drug-resistant strains (combined MDR and XDR strains). Our results advance the current understanding of the effect of drug resistance on bacterial metabolism and open avenues for the detection of drug resistance biomarkers.

New insights in gene expression alteration as effect of doxorubicin drug resistance in triple negative breast cancer cells

BackgroundTriple negative breast cancer (TNBC) is a heterogeneous disease with aggressive behavior and an unfavorable prognosis rate. Due to the lack of surface receptors, TNBC must be intensely investigated in order to establish a suitable treatment for patients with this pathology. Chemoresistance is an important reason for therapeutic failure in TNBC.MethodThe aim of this study was to investigate the effect of doxorubicin in TNBC cell lines and to highlight cellular and molecular alterations after a long exposure to doxorubicin.ResultsThe results revealed that doxorubicin significantly increased the half maximal inhibitory concentration (IC50) values at P12 and P24 compared to parenteral cells P0. Modifications in gene expression were investigated through microarray technique, and for detection of mutational pattern was used Next Generation Sequencing (NGS). 196 upregulated and 115 downregulated genes were observed as effect of multiple dose exposure, and 15 overexpressed genes were found to be involved in drug resistance. Also, the presence of some additional mutations in both cell lines was observed.ConclusionThe outcomes of this research may provide novel biomarkers for drug resistance in TNBC. Also, this activity can highlight the potential mechanisms associated with drug resistance, as well as the potential therapies to counteract these mechanisms.

Analysis of Multiplexed Single Cell RNA Sequencing Clinical Correlative Data in AML Reveals Biomarkers of Resistance

Single cell RNA sequencing (scRNA-seq) is a powerful method to understand gene expression changes in specific subsets of heterogeneous cell populations and to provide novel insight into mechanisms of drug resistance. However, substantial cost and interpatient variability have limited its application as a correlate for prospective clinical trials. To overcome these challenges, we employed a genetic polymorphism-based multiplexing approach to assay peripheral blood samples prospectively collected from patients with relapsed/refractory AML treated on a Phase 1b study using the anti-hepatocyte growth factor monoclonal antibody, Ficlatuzumab (NCT02109627). Ficlatuzumab was administered on study days 1, 15, 29 and 42-44 in combination with high-dose cytarabine. Peripheral blood was collected from 11 subjects on study days 0, 1, 2, 3 and 42-44. N = 7 subjects achieved a complete response to therapy and N = 4 did not respond to therapy. A peripheral blood sample from a healthy volunteer was collected and processed in parallel. 57 samples were multiplexed into 5 pools of 11 to 12 samples using a Latin square design to maximize genetic diversity within each pool and minimize batch effects. Each pool was assayed in duplicate on a 10X Chromium single cell isolation system using 3'-capture technology, targeting 40,000 cells per replicate pool. After initial bioinformatic processing, 175,667 unique cell barcodes were recovered. Genotype-free demultiplexing was performed using Freemuxlet (https://github.com/yelabucsf/popscle). Single nucleotide variants were annotated within the aligned reads from each pool using the 1000 Genomes variant database. A Bayesian clustering algorithm was applied to assign each cell to a group of cells with like genotype. Reference sample genotypes were determined using the Infinium OmniExpressExome-8 BeadChip (Illumina) and these were used to map each cluster to known subject identity. This approach unambiguously assigned 105,363 cells (60.0%) to single subjects and 60,787 (34.6%) to inter-sample doublets. 103,415 cells were retained after removal of intra-sample doublets and low-quality cells. Dimensionality reduction and clustering identified 3 groups of cells that expressed AML blast markers including CD33, CD34, KIT and HLA-DR. We hypothesized that induction of HGF expression by AML blasts might be a mechanism of resistance to anti-HGF therapy. AML blasts were stratified by treatment day and multivariable regression was performed using cluster assignment as a potential confounder. This showed that non-response to study therapy was independently correlated with higher HGF levels on study D0 (q = 0.008), D1 (q = 0.02), and D42-44 (q = 5x10-7). To identify additional biomarkers of resistance to anti-HGF therapy, we performed unsupervised gene module analysis and found 20 groups of genes that were co-regulated within the dataset. One module was strongly induced in non-responders compared to responders at D0 (q = 0), D1 (q = 1x10-278), and D42-44 (q = 0). This module was highly enriched for genes related to type-1 interferon signaling and antiviral response including IL6, IRF7, IRF2, STAT1, STAT2 and APOBEC3A. Unsupervised hierarchical clustering based on gene module scores segregated non-responders from complete responders and showed that the normal control cells were most similar to complete responders at D42-44. These data suggest that multiplexing using genetic polymorphisms increases the number of scRNA-seq samples it is feasible to analyze in the context of a prospective clinical trial. Gene module analysis is able to identify pathways as potential biomarkers of drug resistance in an unsupervised way. These approaches will aid studies in which interpatient variability is a challenge to interpretation of scRNA-seq data. Disclosures Andreadis: Merck: Research Funding; Gilead/Kite: Consultancy; Karyopharm: Honoraria; Jazz Pharmaceuticals: Honoraria; Novartis: Research Funding; Genentech: Consultancy, Current equity holder in publicly-traded company; BMS/Celgene/Juno: Honoraria, Research Funding; Incyte: Consultancy.

Ex vivo cultures and drug testing of primary acute myeloid leukemia samples: Current techniques and implications for experimental design and outcome.

New treatment options of acute myeloid leukemia (AML) are rapidly emerging. Pre-clinical models such as ex vivo cultures are extensively used towards the development of novel drugs and to study synergistic drug combinations, as well as to discover biomarkers for both drug response and anti-cancer drug resistance. Although these approaches empower efficient investigation of multiple drugs in a multitude of primary AML samples, their translational value and reproducibility are hampered by the lack of standardized methodologies and by culture system-specific behavior of AML cells and chemotherapeutic drugs. Moreover, distinct research questions require specific methods which rely on specific technical knowledge and skills. To address these aspects, we herein review commonly used culture techniques in light of diverse research questions. In addition, culture-dependent effects on drug resistance towards commonly used drugs in the treatment of AML are summarized including several pitfalls that may arise because of culture technique artifacts. The primary aim of the current review is to provide practical guidelines for ex vivo primary AML culture experimental design.

Marine Sediment-Derived Streptomyces Strain Produces Angucycline Antibiotics against Multidrug-Resistant Staphylococcus aureus Harboring SCCmec Type 1 Gene

The Philippine archipelago is geographically positioned in the tropics with rich areas of marine biodiversity. Its marine sediments harbor actinomycetes that exhibit antibacterial activity. Screening of actinomycetes isolated from marine sediments collected near the coast of Islas de Gigantes, Iloilo showed one isolate that exhibited high activity against the multidrug-resistant Staphylococcus aureus (MRSA) strain carrying the Staphylococcal Cassette Chromosome mec (SCCmec) type 1 gene, a biomarker for drug resistance. The isolate was identified as Streptomyces sp. strain DSD011 based on its 16s rRNA and protein-coding genes (atpD, recA, rpoB, and trpB) sequences, and was found to be a new species of salt-tolerant marine Streptomyces. Further, the strain harbors both non-ribosomal peptide synthetase (NRPS) and type II polyketide synthase (PKS) in its genome. The targeted chromatographic isolation and chemical investigations by Liquid Chromatography Mass Spectrometry-Time of Flight (LCMS-TOF), tandem mass spectrometry (MS/MS), and Global Natural Product Social molecular networking (GNPS) of the antibiotics produced by the strain afforded the two polycyclic aromatic polyketide angucycline glycosides, fridamycin A (1) and fridamycin D (2), which are products of type II PKS biosynthesis. Compounds 1 and 2 displayed antibacterial activity against MRSA with minimum inhibitory concentration (MIC) of 500 μg/mL and 62.5 μg/mL, respectively. These results suggest that the underexplored marine sediments near the coast of Islas de Gigantes, Iloilo offer access to undiscovered Streptomyces species that are invaluable sources of antibiotic leads.

Abstract 4421: Development of a clinical-genomic database to study tumor evolution and molecular biomarkers of drug resistance in a real-world setting

Abstract Background: Real-world evidence (RWE), specifically the integration of clinical and molecular data, plays an increasingly important role in elucidating the molecular landscape of advanced solid tumors, at diagnosis and at progression, and furthering precision oncology research. However, reliance on tissue genomic testing results within these RWE databases significantly limits our understanding of tumor evolution as tissue profiles are typically limited to a single time point, generally at diagnosis, and biopsies are not routinely completed at progression. Circulating tumor DNA (ctDNA) analysis at diagnosis and progression is an alternative to serial tissue testing. Studying the real-world data derived from ctDNA testing results can provide additional information, specifically around tumor evolution and mechanisms of innate and acquired resistance in response to intervening therapies (targeted and non-targeted). Methods: Anonymized results from patients consecutively tested with Guardant360®, a CLIA-certified, CAP-accredited, NYSDOH-approved ctDNA test indicated for patients with advanced and metastatic solid tumor cancers (Guardant Health, Redwood City, California) were analyzed. Using a secure and HIPAA-compliant methodology, these results were then linked to a de-identified encounters database containing medical and pharmacy claims to provide a longitudinal view of patients' journeys, including diagnosis, treatments, and real-world outcomes. Results: Of 85,874 patients, the disease groups most highly represented were lung, breast, colorectal, prostate, and pancreas cancers. 48,317 patients (56.3%) had a record of treatment with an antineoplastic treatment (i.e. chemo, hormonal, small molecule, or immuno-therapy). Of patients with a record of therapy, 14,608 (30.2%) had a record of therapy following, but none prior to, the Guardant360 test date, 14,493 (30.0%) had a record of therapy prior to, but not following theGuardant360 test date, and 19,216 (39.8%) had a record of therapy both before and after Guardant360 test date. Conclusions: In a cohort of patients who underwent ctDNA testing and for whom treatment information was available, post-therapy molecular results were available in 69.8%. The availability of genomic information following systemic therapy suggest that this dataset is a viable resource to study drug resistance and tumor evolution in the real-world setting. Citation Format: Naveen Kumar, Rajesh Kucharlapati, Aaron Hardin, Victoria M. Raymond, Stephen Fairclough, Kathryn Lang. Development of a clinical-genomic database to study tumor evolution and molecular biomarkers of drug resistance in a real-world setting [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4421.