Single-cell analyses reveal increased intratumoral heterogeneity after the onset of therapy resistance in small-cell lung cancer

Stewart, C. Allison; Xi, Yuanxin; Sivajothi, Santhosh; Sivakamasundari, V.; Fujimoto, Junya; Bolisetty, Mohan; Hartsfield, Patrice M.; Balasubramaniyan, Veerakumar; Chalishazar, Milind D.; Moran, César A.; Kalhor, Neda; Stewart, John; Tran, Hai T.; Swisher, Stephen G.; Roth, Jack A.; Zhang, Jianjun; Groot, John de; Glisson, Bonnie S.; Oliver, Trudy G.; Heymach, John V.; Wistuba, Ignacio I.; Robson, Paul; Wang, Jing; Byers, Lauren A.

doi:10.1038/s43018-019-0020-z

Cited by 258 publications

(323 citation statements)

References 55 publications

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“…interpreted as a more homogeneous distribution across the tumor area in both groups (ANOVA: p = 0.0039). Increased intra-tumor heterogeneity has previously been identified as an important indicator for therapy resistance and poor overall survival (46)(47)(48). However, for L-phenylalanine, we did not observe a difference in heterogeneity (dynamic range) between both groups (Student's t-test: p = 0.9443; Fig.…”

Section: Resultscontrasting

confidence: 49%

Sequential 3D OrbiSIMS and LESA-MS/MS-based metabolomics for prediction of brain tumor relapse from sample-limited primary tissue archives

Meurs¹,

Scurr²,

Lourdusamy³

et al. 2020

Preprint

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Surgically-resected biopsies from childhood brain tumors are archived in a formalin-fixed paraffin-embedded (FFPE) state. Identified key tumor regions are conserved through the fabrication of tissue microarrays (TMA). The vast amount of TMA libraries available have the potential to be used for metabolite profiling; however, due to incompatibility of TMAs with current analysis strategies, the potential has been unexplored. The recent emergence of liquid extraction surface analysis tandem mass spectrometry (LESA-MS/MS) and Orbitrap secondary ion mass spectrometry (3D OrbiSIMS) allows for a novel untargeted metabolite profiling and imaging approach for characterization of tumor TMAs. This strategy employs serial mass spectrometry (MS) analysis, with the high mass resolving imaging power of 3D OrbiSIMS combining complementarity, with the detection of a greater number of metabolites using LESA-MS/MS. Using multivariate analysis on data generated from both techniques permits the identification of metabolites that group patients based on eventual tumor recurrence, leading to the discovery of novel affected metabolic pathways and the prediction of tumor recurrence with high confidence. Moreover, both techniques reveal a unique set of classifiers and metabolic pathways for predicting pediatric ependymoma relapse from a set of primary tumors. The serial MS strategy opens new opportunities to retrospectively link molecular data from any FFPE TMA library with clinical outcomes and to discover novel drug targets with the aim of developing stratified drug treatments.

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Section: Resultscontrasting

confidence: 49%

Sequential 3D OrbiSIMS and LESA-MS/MS-based metabolomics for prediction of brain tumor relapse from sample-limited primary tissue archives

Meurs¹,

Scurr²,

Lourdusamy³

et al. 2020

Preprint

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“…Each group was subsampled to 20,000 total cells. EMT score was calculated based on the EMT signature as described previously 52,83 . Cell-specific expression of SFTPC (alveolar type II cells), FOXJI, PIFO (ciliated cells), and SCGB1A1 (club cells) were visualized in tSNE feature plots to identify epithelial clusters containing ACE2-positive cells.…”

Section: Single-cell Rnaseq Analysismentioning

confidence: 99%

Lung cancer models reveal SARS-CoV-2-induced EMT contributes to COVID-19 pathophysiology

Stewart

Gay

Ramkumar

et al. 2020

Preprint

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COVID-19 is an infectious disease caused by SARS-CoV-2, which enters host cells via the cell surface proteins ACE2 and TMPRSS2. Using normal and malignant models and tissues from the aerodigestive and respiratory tracts, we investigated the expression and regulation of ACE2 and TMPRSS2. We find that ACE2 expression is restricted to a select population of highly epithelial cells and is repressed by ZEB1, in concert with ZEB1's established role in promoting epithelial to mesenchymal transition (EMT). Notably, infection of lung cancer cells with SARS-CoV-2 induces metabolic and transcriptional changes consistent with EMT, including upregulation of ZEB1 and AXL, thereby downregulating ACE2 postinfection. This suggests a novel model of SARS-CoV-2 pathogenesis in which infected cells shift toward an increasingly mesenchymal state and lose ACE2 expression, along with its acute respiratory distress syndrome-protective effect, in a ZEB1-dependent manner. AXL-inhibition and ZEB1-reduction, as with bemcentinib, offers a potential strategy to reverse this effect.

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“…[36,37] PDX models have been applied in molecular and genetic investigations of drug resistance in previous studies. [38][39][40] To study the accumulation of nanoparticles, a PDX-tumorbearing mouse was intravenously injected with PolyPt/Ru nanoparticles from the tail vein. Fluorescence images of the mouse model (right) and a control mouse (left) were taken over time after injection (Figure 4a).…”

Section: (6 Of 9)mentioning

confidence: 99%

Fighting against Drug‐Resistant Tumors using a Dual‐Responsive Pt(IV)/Ru(II) Bimetallic Polymer

et al. 2020

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First, proteins such as serum albumin in blood deactivate cisplatin. [5] Second, cisplatin cannot be efficiently taken up by cisplatin-resistant cancer cells. [6] Third, intracellular biomolecules such as metallothionein (MT) and glutathione (GSH) may strongly bind and sequester cisplatin. [7] Fourth, the DNA of cancer cells that are damaged by cisplatin, can be repaired by proteins. [8] All these deactivation pathways hinder the curative effects of cisplatin. Some strategies have been developed to overcome the abovementioned deactivation pathways. For example, Pt(IV) prodrugs, which release cisplatin in cancer cells, have been developed. [9-12] Pt(IV) prodrugs are more resistant to ligand substitution reactions than cisplatin because Pt(IV) centers are saturated and kinetically more inert. [1] Thus, Pt(IV) can minimize unwanted side reactions with biomolecules prior to DNA binding. Another strategy to overcome deactivation is to combine cisplatin with other anticancer agents such as paclitaxel, 5-fluorouracil, gemcitabine or ruthenium complexes. [13-16] Mixtures of anticancer agents possess multiple targets and actions; this strategy strengthens the therapeutic effects via the different anticancer mechanisms of the different agents. [14] A third strategy to overcome deactivation is to use nanocarriers for the delivery of cisplatin. [17,18] Some Drug resistance is a major problem in cancer treatment. Herein, the design of a dual-responsive Pt(IV)/Ru(II) bimetallic polymer (PolyPt/Ru) to treat cisplatin-resistant tumors in a patient-derived xenograft (PDX) model is reported. PolyPt/Ru is an amphiphilic ABA-type triblock copolymer. The hydrophilic A blocks consist of biocompatible poly(ethylene glycol) (PEG). The hydrophobic B block contains reduction-responsive Pt(IV) and red-light-responsive Ru(II) moieties. PolyPt/Ru self-assembles into nanoparticles that are efficiently taken up by cisplatin-resistant cancer cells. Irradiation of cancer cells containing PolyPt/Ru nanoparticles with red light generates 1 O 2 , induces polymer degradation, and triggers the release of the Ru(II) anticancer agent. Meanwhile, the anticancer drug, cisplatin, is released in the intracellular environment via reduction of the Pt(IV) moieties. The released Ru(II) anticancer agent, cisplatin, and the generated 1 O 2 have different anticancer mechanisms; their synergistic effects inhibit the growth of drugresistant cancer cells. Furthermore, PolyPt/Ru nanoparticles inhibit tumor growth in a PDX mouse model because they circulate in the bloodstream, accumulate at tumor sites, exhibit good biocompatibility, and do not cause side effects. The results demonstrate that the development of stimuli-responsive multi-metallic polymers provides a new strategy to overcome drug resistance.

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Single-cell analyses reveal increased intratumoral heterogeneity after the onset of therapy resistance in small-cell lung cancer

Cited by 258 publications

References 55 publications

Sequential 3D OrbiSIMS and LESA-MS/MS-based metabolomics for prediction of brain tumor relapse from sample-limited primary tissue archives

Sequential 3D OrbiSIMS and LESA-MS/MS-based metabolomics for prediction of brain tumor relapse from sample-limited primary tissue archives

Lung cancer models reveal SARS-CoV-2-induced EMT contributes to COVID-19 pathophysiology

Fighting against Drug‐Resistant Tumors using a Dual‐Responsive Pt(IV)/Ru(II) Bimetallic Polymer

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