Clonal Evolution in 207 Cases of Refractory or Relapsed Acute Myeloid Leukemia.

Clonal evolution (CE) is a driving force behind the development and progression of acute myeloid leukemia (AML). Advances in molecular and cytogenetic assays have improved the depth and breadth of detection of CE in AML, which is defined here as a detected change in cytogenetic or molecular profile at relapsed or refractory (RR) disease. In this study, we demonstrate the clinical impact of CE in a cohort of patients with RR AML treated between 2013 and 2023. We discovered CE is significantly more frequent in relapsed disease (58.2%, [46.6%, 69.2%]) than in refractory disease (21.1%, [14.4%, 29.2%], p < 0.001). CE negatively impacts prognosis when detected by conventional karyotyping in refractory disease (4.2 vs. 13.9 months, p < 0.011). In contrast with prior literature, CE had no impact on overall survival if detected in relapsed disease. Surprisingly, those who achieved negative measurable residual disease (MRD) were no more likely to eliminate their original clone than those who did not (p = 1). We found several cytogenetic and molecular signatures which may predispose to CE: aberrations of chromosome 17, trisomy 8, TP53, KRAS, and FLT3-TKD. Finally, physicians were less likely to retreat those with CE with IC after receiving IC as first-line therapy (35.0% vs. 70.9%, p = 0.004). This study illustrates the role of CE in chemotherapy-resistant AML; we identify unique cytogenetic and molecular signatures that define a subset of patients associated with a dismal prognosis. As next-generation sequencing panels expand and new methods to characterize cytogenetic abnormalities emerge, our findings establish a basis for future studies investigating the prognostic and therapeutic impact of CE.

Single cell biomass tracking allows identification and isolation of rare targeted therapy-resistant DLBCL cells within a mixed population.

Adaptive resistance is a major limitation in the use of targeted therapies for cancer. Using real time biomass tracking, we demonstrate the isolation and identification of rare (1% fraction) diffuse large B cell lymphoma cells resistant to the PI3K inhibitor idelalisib, from an otherwise sensitive population. This technique allows direct study of these rare, drug tolerant cells.

Identifying fates of cancer cells exposed to mitotic inhibitors by quantitative phase imaging.

Cell cycle deregulation is a cancer hallmark that has stimulated the development of mitotic inhibitors with differing mechanisms of action. Quantitative phase imaging (QPI) is an emerging approach for determining cancer cell sensitivities to chemotherapies in vitro. Cancer cell fates in response to mitotic inhibitors are agent- and dose-dependent. Fates that lead to chromosomal instabilities may result in a survival advantage and drug resistance. Conventional techniques for quantifying cell fates are incompatible with growth inhibition assays that produce binary live/dead results. Therefore, we used QPI to quantify post-mitotic fates of G0/G1 synchronized HeLa cervical adenocarcinoma and M202 melanoma cells during 24 h of escalating-dose exposures to mitotic inhibitors, including microtubule inhibitors paclitaxel and colchicine, and an Aurora kinase A inhibitor, VX-680. QPI determined cell fates by measuring changes in cell biomass, morphology, and mean phase-shift. Cell fates fell into three groups: (1) bipolar division from drug failure; (2) cell death or sustained mitotic arrest; and (3) aberrant endocycling or multipolar division. In this proof-of-concept study, colchicine was most effective in producing desirable outcomes of sustained mitotic arrest or death throughout its dosing range, whereas both paclitaxel and VX-680 yielded dose-dependent multipolar divisions or endocycling, respectively. Furthermore, rapid completion of mitosis associated with bipolar divisions whereas prolonged mitosis associated with multipolar divisions or cell death. Overall, QPI measurement of drug-induced cancer cell fates provides a tool to inform the development of candidate agents by quantifying the dosing ranges over which suboptimal inhibitor choices lead to undesirable, aberrant cancer cell fates.

Free-Standing Kinked Silicon Nanowires for Probing Inter- and Intracellular Force Dynamics.

Silicon nanowires (SiNWs) have emerged as a new class of materials with important applications in biology and medicine with current efforts having focused primarily on using substrate bound SiNW devices. However, developing devices capable of free-standing inter- and intracellular operation is an important next step in designing new synthetic cellular materials and tools for biophysical characterization. To demonstrate this, here we show that label free SiNWs can be internalized in multiple cell lines, forming robust cytoskeletal interfaces, and when kinked can serve as free-standing inter- and intracellular force probes capable of continuous extended (>1 h) force monitoring. Our results show that intercellular interactions exhibit ratcheting like behavior with force peaks of ∼69.6 pN/SiNW, while intracellular force peaks of ∼116.9 pN/SiNW were recorded during smooth muscle contraction. To accomplish this, we have introduced a simple single-capture dark-field/phase contrast optical imaging modality, scatter enhanced phase contrast (SEPC), which enables the simultaneous visualization of both cellular components and inorganic nanostructures. This approach demonstrates that rationally designed devices capable of substrate-independent operation are achievable, providing a simple and scalable method for continuous inter- and intracellular force dynamics studies.

Drug screening at single-organoid resolution via bioprinting and interferometry.

High throughput drug screening is an established approach to investigate tumor biology and identify therapeutic leads. Traditional platforms use two-dimensional cultures which do not accurately reflect the biology of human tumors. More clinically relevant model systems such as three-dimensional tumor organoids can be difficult to scale and screen. Manually seeded organoids coupled to destructive endpoint assays allow for the characterization of treatment response, but do not capture transitory changes and intra-sample heterogeneity underlying clinically observed resistance to therapy. We present a pipeline to generate bioprinted tumor organoids linked to label-free, time-resolved imaging via high-speed live cell interferometry (HSLCI) and machine learning-based quantitation of individual organoids. Bioprinting cells gives rise to 3D structures with unaltered tumor histology and gene expression profiles. HSLCI imaging in tandem with machine learning-based segmentation and classification tools enables accurate, label-free parallel mass measurements for thousands of organoids. We demonstrate that this strategy identifies organoids transiently or persistently sensitive or resistant to specific therapies, information that could be used to guide rapid therapy selection.

Tumor cell escape from therapy-induced senescence.

H460 non-small cell lung, HCT116 colon and 4T1 breast tumor cell lines induced into senescence by exposure to either etoposide or doxorubicin were able to recover proliferative capacity both in mass culture and when enriched for the senescence-like phenotype by flow cytometry (based on ß-galactosidase staining and cell size, and a senescence-associated reporter, BTG1-RFP). Recovery was further established using both real-time microscopy and High-Speed Live-Cell Interferometry (HSLCI) and was shown to be accompanied by the attenuation of the Senescence-Associated Secretory Phenotype (SASP). Cells enriched for the senescence-like phenotype were also capable of forming tumors when implanted in both immunodeficient and immunocompetent mice. As chemotherapy-induced senescence has been identified in patient tumors, our results suggest that certain senescence-like phenotypes may not reflect a terminal state of growth arrest, as cells that recover with self-renewal capacity may ultimately contribute to disease recurrence.

Functional and structural characterization of osteocytic MLO-Y4 cell proteins encoded by genes differentially expressed in response to mechanical signals in vitro.

The anabolic response of bone to mechanical load is partially the result of osteocyte response to fluid flow-induced shear stress. Understanding signaling pathways activated in osteocytes exposed to fluid flow could identify novel signaling pathways involved in the response of bone to mechanical load. Bioinformatics allows for a unique perspective and provides key first steps in understanding these signaling pathways. We examined proteins encoded by genes differentially expressed in response to fluid flow in murine osteocytic MLO-Y4 cells. We considered structural and functional characteristics including putative intrinsic disorder, evolutionary conservation, interconnectedness in protein-protein interaction networks, and cellular localization. Our analysis suggests that proteins encoded by fluid flow activated genes have lower than expected conservation, are depleted in intrinsic disorder, maintain typical levels of connectivity for the murine proteome, and are found in the cytoplasm and extracellular space. Pathway analyses reveal that these proteins are associated with cellular response to stress, chemokine and cytokine activity, enzyme binding, and osteoclast differentiation. The lower than expected disorder of proteins encoded by flow activated genes suggests they are relatively specialized.

Live Cell Mass Accumulation Measurement Non-Invasively Predicts Carboplatin Sensitivity in Triple-Negative Breast Cancer Patient-Derived Xenografts.

Prompt and repeated assessments of tumor sensitivity to available therapeutics could reduce patient morbidity and mortality by quickly identifying therapeutic resistance and optimizing treatment regimens. Analysis of changes in cancer cell biomass has shown promise in assessing drug sensitivity and fulfilling these requirements. However, a major limitation of previous studies in solid tumors, which comprise 90% of cancers, is the use of cancer cell lines rather than freshly isolated tumor material. As a result, existing biomass protocols are not obviously extensible to real patient tumors owing to potential artifacts that would be generated by the removal of cells from their microenvironment and the deleterious effects of excision and purification. In this present work, we show that simple excision of human triple-negative breast cancer (TNBC) tumors growing in immunodeficient mouse, patient-derived xenograft (PDX) models, followed by enzymatic disaggregation into single cell suspension, is enabling for rapid and accurate biomass accumulation-based predictions of in vivo sensitivity to the chemotherapeutic drug carboplatin. We successfully correlate in vitro biomass results with in vivo treatment results in three TNBC PDX models that have differential sensitivity to this drug. With a maximum turnaround time of 40 h from tumor excision to useable results and a fully-automated analysis pipeline, the assay described here has significant potential for translation to clinical practice.