Phenotyping EMT and MET cellular states in lung cancer patient liquid biopsies at a personalized level using mass cytometry.

Malignant pleural effusions (MPEs) can be utilized as liquid biopsy for phenotyping malignant cells and for precision immunotherapy, yet MPEs are inadequately studied at the single-cell proteomic level. Here we leverage mass cytometry to interrogate immune and epithelial cellular profiles of primary tumors and pleural effusions (PEs) from early and late-stage non-small cell lung cancer (NSCLC) patients, with the goal of assessing epithelial-mesenchymal transition (EMT) and mesenchymal-epithelial transition (MET) states in patient specimens. By using the EMT-MET reference map PHENOSTAMP, we observe a variety of EMT states in cytokeratin positive (CK+) cells, and report for the first time MET-enriched CK+ cells in MPEs. We show that these states may be relevant to disease stage and therapy response. Furthermore, we found that the fraction of CD33+ myeloid cells in PEs was positively correlated to the fraction of CK+ cells. Longitudinal analysis of MPEs drawn 2 months apart from a patient undergoing therapy, revealed that CK+ cells acquired heterogeneous EMT features during treatment. We present this work as a feasibility study that justifies deeper characterization of EMT and MET states in malignant cells found in PEs as a promising clinical platform to better evaluate disease progression and treatment response at a personalized level.

Phenotypic maps for precision medicine: a promising systems biology tool for assessing therapy response and resistance at a personalized level.

In this perspective we discuss how tumor heterogeneity and therapy resistance necessitate a focus on more personalized approaches, prompting a shift toward precision medicine. At the heart of the shift towards personalized medicine, omics-driven systems biology becomes a driving force as it leverages high-throughput technologies and novel bioinformatics tools. These enable the creation of systems-based maps, providing a comprehensive view of individual tumor's functional plasticity. We highlight the innovative PHENOSTAMP program, which leverages high-dimensional data to construct a visually intuitive and user-friendly map. This map was created to encapsulate complex transitional states in cancer cells, such as Epithelial-Mesenchymal Transition (EMT) and Mesenchymal-Epithelial Transition (MET), offering a visually intuitive way to understand disease progression and therapeutic responses at single-cell resolution in relation to EMT-related single-cell phenotypes. Most importantly, PHENOSTAMP functions as a reference map, which allows researchers and clinicians to assess one clinical specimen at a time in relation to their phenotypic heterogeneity, setting the foundation on constructing phenotypic maps for personalized medicine. This perspective argues that such dynamic predictive maps could also catalyze the development of personalized cancer treatment. They hold the potential to transform our understanding of cancer biology, providing a foundation for a future where therapy is tailored to each patient's unique molecular and cellular tumor profile. As our knowledge of cancer expands, these maps can be continually refined, ensuring they remain a valuable tool in precision oncology.

Modeling collective cell behavior in cancer: Perspectives from an interdisciplinary conversation.

Collective cell behavior contributes to all stages of cancer progression. Understanding how collective behavior emerges through cell-cell interactions and decision-making will advance our understanding of cancer biology and provide new therapeutic approaches. Here, we summarize an interdisciplinary discussion on multicellular behavior in cancer, draw lessons from other scientific disciplines, and identify future directions.

Therapeutic efficacy of the humanized JAA-F11 anti-Thomsen-Friedenreich antibody constructs H2aL2a and H3L3 in human breast and lung cancer xenograft models.

The Thomsen-Friedenreich antigen (TF-Ag-α) is found on ~85% of human carcinomas but is cryptic on normal tissue. The humanized highly specific hJAA-F11-H2aL2a and -H3L3 antibodies target TF-Ag-α without binding to TF-Ag-beta (found on surface glycolipids of some normal cells). The relative affinity of H3L3 is 17 times that of H2aL2a, which would seem to favor superior efficacy, however, increased affinity can result in less tumor penetration. To assess the potential therapeutic efficacy of these antibodies, four human cancer- mouse xenograft models were treated with H2aL2a and H3L3. The tumor xenograft models used were human non-small cell lung cancer, H520, and small cell lung cancer, HTB171 in nude mice and human triple negative breast cancer, MDA-MB-231 and HCC1806 in SCID mice. H2aL2a significantly decreased tumor growth in both breast and both lung cancer models. H2aL2a showed statistically equal or better efficacy than H3L3 and has superior production capabilities. These results suggest that H2aL2a may be superior as a naked antibody, as an antibody drug conjugate or as a radiolabeled antibody, however the higher affinity of H3L3 may lead to better efficacy in bi-specific therapies in which the binding is decreased due to the presence of only one TF-Ag-α binding site.

Multiomics Analysis of Spatially Distinct Stromal Cells Reveals Tumor-Induced O-Glycosylation of the CDK4-pRB Axis in Fibroblasts at the Invasive Tumor Edge.

The invasive leading edge represents a potential gateway for tumor metastasis. The role of fibroblasts from the tumor edge in promoting cancer invasion and metastasis has not been comprehensively elucidated. We hypothesize that cross-talk between tumor and stromal cells within the tumor microenvironment results in activation of key biological pathways depending on their position in the tumor (edge vs. core). Here we highlight phenotypic differences between tumor-adjacent-fibroblasts (TAF) from the invasive edge and tumor core fibroblasts from the tumor core, established from human lung adenocarcinomas. A multiomics approach that includes genomics, proteomics, and O-glycoproteomics was used to characterize cross-talk between TAFs and cancer cells. These analyses showed that O-glycosylation, an essential posttranslational modification resulting from sugar metabolism, alters key biological pathways including the cyclin-dependent kinase 4 (CDK4) and phosphorylated retinoblastoma protein axis in the stroma and indirectly modulates proinvasive features of cancer cells. In summary, the O-glycoproteome represents a new consideration for important biological processes involved in tumor-stroma cross-talk and a potential avenue to improve the anticancer efficacy of CDK4 inhibitors. SIGNIFICANCE: A multiomics analysis of spatially distinct fibroblasts establishes the importance of the stromal O-glycoproteome in tumor-stroma interactions at the leading edge and provides potential strategies to improve cancer treatment. See related commentary by De Wever, p. 537.

From imaging a single cell to implementing precision medicine: an exciting new era.

In the age of high-throughput, single-cell biology, single-cell imaging has evolved not only in terms of technological advancements but also in its translational applications. The synchronous advancements of imaging and computational biology have produced opportunities of merging the two, providing the scientific community with tools towards observing, understanding, and predicting cellular and tissue phenotypes and behaviors. Furthermore, multiplexed single-cell imaging and machine learning algorithms now enable patient stratification and predictive diagnostics of clinical specimens. Here, we provide an overall summary of the advances in single-cell imaging, with a focus on high-throughput microscopy phenomics and multiplexed proteomic spatial imaging platforms. We also review various computational tools that have been developed in recent years for image processing and downstream applications used in biomedical sciences. Finally, we discuss how harnessing systems biology approaches and data integration across disciplines can further strengthen the exciting applications and future implementation of single-cell imaging on precision medicine.

Mapping lung cancer epithelial-mesenchymal transition states and trajectories with single-cell resolution.

Elucidating the spectrum of epithelial-mesenchymal transition (EMT) and mesenchymal-epithelial transition (MET) states in clinical samples promises insights on cancer progression and drug resistance. Using mass cytometry time-course analysis, we resolve lung cancer EMT states through TGFß-treatment and identify, through TGFß-withdrawal, a distinct MET state. We demonstrate significant differences between EMT and MET trajectories using a computational tool (TRACER) for reconstructing trajectories between cell states. In addition, we construct a lung cancer reference map of EMT and MET states referred to as the EMT-MET PHENOtypic STAte MaP (PHENOSTAMP). Using a neural net algorithm, we project clinical samples onto the EMT-MET PHENOSTAMP to characterize their phenotypic profile with single-cell resolution in terms of our in vitro EMT-MET analysis. In summary, we provide a framework to phenotypically characterize clinical samples in the context of in vitro EMT-MET findings which could help assess clinical relevance of EMT in cancer in future studies.

DRUG-NEM: Optimizing drug combinations using single-cell perturbation response to account for intratumoral heterogeneity.

An individual malignant tumor is composed of a heterogeneous collection of single cells with distinct molecular and phenotypic features, a phenomenon termed intratumoral heterogeneity. Intratumoral heterogeneity poses challenges for cancer treatment, motivating the need for combination therapies. Single-cell technologies are now available to guide effective drug combinations by accounting for intratumoral heterogeneity through the analysis of the signaling perturbations of an individual tumor sample screened by a drug panel. In particular, Mass Cytometry Time-of-Flight (CyTOF) is a high-throughput single-cell technology that enables the simultaneous measurements of multiple ([Formula: see text]40) intracellular and surface markers at the level of single cells for hundreds of thousands of cells in a sample. We developed a computational framework, entitled Drug Nested Effects Models (DRUG-NEM), to analyze CyTOF single-drug perturbation data for the purpose of individualizing drug combinations. DRUG-NEM optimizes drug combinations by choosing the minimum number of drugs that produce the maximal desired intracellular effects based on nested effects modeling. We demonstrate the performance of DRUG-NEM using single-cell drug perturbation data from tumor cell lines and primary leukemia samples.

Preclinical Analysis of JAA-F11, a Specific Anti-Thomsen-Friedenreich Antibody via Immunohistochemistry and In Vivo Imaging.

The tumor specificity of JAA-F11, a novel monoclonal antibody specific for the Thomsen-Friedenreich cancer antigen (TF-Ag-alpha linked), has been comprehensively studied by in vitro immunohistochemical (IHC) staining of human tumor and normal tissue microarrays and in vivo biodistribution and imaging by micro-positron emission tomography imaging in breast and lung tumor models in mice. The IHC analysis detailed herein is the comprehensive biological analysis of the tumor specificity of JAA-F11 antibody performed as JAA-F11 is progressing towards preclinical safety testing and clinical trials. Wide tumor reactivity of JAA-F11, relative to the matched mouse IgG3 (control), was observed in 85% of 1269 cases of breast, lung, prostate, colon, bladder, and ovarian cancer. Staining on tissues from breast cancer cases was similar regardless of hormonal or Her2 status, and this is particularly important in finding a target on the currently untargetable triple-negative breast cancer subtype. Humanization of JAA-F11 was recently carried out as explained in a companion paper "Humanization of JAA-F11, a Highly Specific Anti-Thomsen-Friedenreich Pancarcinoma Antibody and In Vitro Efficacy Analysis" (Neoplasia 19: 716-733, 2017), and it was confirmed that humanization did not affect chemical specificity. IHC studies with humanized JAA-F11 showed similar binding to human breast tumor tissues. In vivo imaging and biodistribution studies in a mouse syngeneic breast cancer model and in a mouse-human xenograft lung cancer model with humanized 124I- JAA-F11 construct confirmed in vitro tumor reactivity and specificity. In conclusion, the tumor reactivity of JAA-F11 supports the continued development of JAA-F11 as a targeted cancer therapeutic for multiple cancers, including those with unmet need.

Humanization of JAA-F11, a Highly Specific Anti-Thomsen-Friedenreich Pancarcinoma Antibody and InVitro Efficacy Analysis.

JAA-F11 is a highly specific mouse monoclonal to the Thomsen-Friedenreich Antigen (TF-Ag) which is an alpha-O-linked disaccharide antigen on the surface of ~80% of human carcinomas, including breast, lung, colon, bladder, ovarian, and prostate cancers, and is cryptic on normal cells. JAA-F11 has potential, when humanized, for cancer immunotherapy for multiple cancer types. Humanization of JAA-F11, was performed utilizing complementarity determining regions grafting on a homology framework. The objective herein is to test the specificity, affinity and biology efficacy of the humanized JAA-F11 (hJAA-F11). Using a 609 target glycan array, 2 hJAA-F11 constructs were shown to have excellent chemical specificity, binding only to TF-Ag alpha-linked structures and not to TF-Ag beta-linked structures. The relative affinity of these hJAA-F11 constructs for TF-Ag was improved over the mouse antibody, while T20 scoring predicted low clinical immunogenicity. The hJAA-F11 constructs produced antibody-dependent cellular cytotoxicity in breast and lung tumor lines shown to express TF-Ag by flow cytometry. Internalization of hJAA-F11 into cancer cells was also shown using a surface binding ELISA and confirmed by immunofluorescence microscopy. Both the naked hJAA-F11 and a maytansine-conjugated antibody (hJAA-F11-DM1) suppressed in vivo tumor progression in a human breast cancer xenograft model in SCID mice. Together, our results support the conclusion that the humanized antibody to the TF-Ag has potential as an adjunct therapy, either directly or as part of an antibody drug conjugate, to treat breast cancer, including triple negative breast cancer which currently has no targeted therapy, as well as lung cancer.

Akt activation by Ca2+/calmodulin-dependent protein kinase kinase 2 (CaMKK2) in ovarian cancer cells.

Hyperactivation of Akt is associated with oncogenic changes in the growth, survival, and chemoresistance of cancer cells. The PI3K/phosphoinositide-dependent kinase (PDK) 1 pathway represents the canonical mechanism for phosphorylation of Akt at its primary activation site, Thr-308. We observed that Ca2+/calmodulin (CaM)-dependent protein kinase kinase 2 (ß) (CaMKK2) is highly expressed in high-grade serous ovarian cancer, and we investigated its role in Akt activation in ovarian cancer (OVCa) cell lines (OVCAR-3, SKOV-3, and Caov-3). Knockdown or pharmacological inhibition of CaMKK2 produced phenotypes expected of Akt inhibition, including reductions in cell growth and cell viability and in the regulation of Akt downstream targets involved in G1/S transition and apoptosis. CaMKK2 knockdown or inhibition decreased Akt phosphorylation at Thr-308 and Ser-473 to extents similar to those of PDK1 knockdown or PI3K inhibition. Combined CaMKK2 and PDK1 knockdown or CaMKK and PI3K inhibition, respectively, produced additive effects on p-Akt and cell growth, consistent with direct Akt phosphorylation by CaMKK2. This conclusion was supported by the absence of effects of CaMKK2 knockdown/inhibition on alternative means of activating Akt via p-Akt Thr-450, p-PDK1 Ser-241, or p-IRS1 Ser-636/639. Recombinant CaMKK2 directly activated recombinant Akt by phosphorylation at Thr-308 in a Ca2+/CaM-dependent manner. In OVCa cells, p-Akt Thr-308 was significantly inhibited by intracellular Ca2+i chelation or CaM inhibition. Ionomycin-induced Ca2+ influx promoted p-Akt, an effect blocked by PDK1, and/or CaMKK2, siRNAs, and by PI3K and/or CaMKK inhibitors. CaMKK2 knockdown potentiated the effects of the chemotherapeutic drugs carboplatin and PX-866 to reduce proliferation and survival of OVCa cells.

Comparative Effectiveness of Up To Three Lines of Chemotherapy Treatment Plans for Metastatic Colorectal Cancer.

Modern chemotherapy agents transformed standard care for metastatic colorectal cancer (mCRC) but raised concerns about the financial burden of the disease. We studied comparative effectiveness of treatment plans that involve up to three lines of therapies and impact of treatment sequencing on health and cost outcomes. We employed a Markov model to represent the dynamically changing health status of mCRC patients and used Monte-Carlo simulation to evaluate various treatment plans consistent with existing guidelines. We calibrated our model by a meta-analysis of published data from an extensive list of clinical trials and measured the effectiveness of each plan in terms of cost per quality-adjusted life year. We examined the sensitivity of our model and results with respect to key parameters in two scenarios serving as base case and worst case for patients' overall and progression-free survivals. The derived efficient frontiers included seven and five treatment plans in base case and worst case, respectively. The incremental cost-effectiveness ratio (ICER) ranged between $26,260 and $152,530 when the treatment plans on the efficient frontiers were compared against the least costly efficient plan in the base case, and between $21,256 and $60,040 in the worst case. All efficient plans were expected to lead to fewer than 2.5 adverse effects and on average successive adverse effects were spaced more than 9 weeks apart from each other in the base case. Based on ICER, all efficient treatment plans exhibit at least 87% chance of being efficient. Sensitivity analyses show that the ICERs were most dependent on drug acquisition cost, distributions of progression-free and overall survivals, and health utilities. We conclude that improvements in health outcomes may come at high incremental costs and are highly dependent in the order treatments are administered.

Nucleoporin 62 and Ca(2+)/calmodulin dependent kinase kinase 2 regulate androgen receptor activity in castrate resistant prostate cancer cells.

BACKGROUND: Re-activation of the transcriptional activity of the androgen receptor (AR) is an important factor mediating progression from androgen-responsive to castrate-resistant prostate cancer (CRPC). However, the mechanisms regulating AR activity in CRPC remain incompletely understood. Ca(2+) /calmodulin-dependent kinase kinase (CaMKK) 2 was previously shown to regulate AR activity in androgen-responsive prostate cancer cells. Our objective was to further explore the basis of this regulation in CRPC cells. METHODS: The abundance of CaMKK2 in nuclear fractions of androgen-responsive prostate cancer and CRPC, cells were determined by subcellular fractionation and Western blotting. CaMKK2 association with nuclear pore complexes (NPCs) and nucleoporins (Nups) including Nup62, were imaged by structured illumination and super-resolution fluorescence microscopy and co-immunoprecipitation, respectively. The abundance and subcellular localization of CaMKK2 and Nup62 in human clinical specimens of prostate cancer was visualized by immunohistochemistry. The role of Nups in the growth and viability of CRPC cells was assessed by RNA interference and cell counting. The involvement of CaMKK2 and Nup62 in regulating AR transcriptional activity was addressed by RNA interference, chromatin immunoprecipitation, androgen response element reporter assay, and Western blotting. RESULTS: CaMKK2 was expressed at higher levels in the nuclear fraction of CPRC C4-2 cells, than in that of androgen-responsive LNCaP cells. In C4-2 cells, CaMKK2 associated with NPCs of the nuclear envelope and physically interacted with Nup62. CaMKK2 and Nup62 demonstrated pronounced, and similar increases in both expression and perinuclear/nuclear localization in human clinical specimens of advanced prostate cancer relative to normal prostate. Knockdown of Nup62, but not of Nups, 98 or 88, reduced growth and viability of C4-2 cells. Knockdown of Nup62 produced a greater reduction of the growth and viability of C4-2 cells than of non-neoplastic RWPE-1 prostatic cells. Nup62, CaMKK2, and the AR were recruited to androgen response elements of the AR target genes, prostate specific antigen, and transmembrane protease, serine 2. Knockdown of CaMKK2 and Nup62 reduced prostate specific antigen expression and AR transcriptional activity driven by androgen response elements from the prostate-specific probasin gene promoter. CONCLUSION: Nup62 and CaMKK2 are required for optimal AR transcriptional activity and a potential mechanism for AR re-activation in CRPC.

A regulatory feedback loop between Ca2+/calmodulin-dependent protein kinase kinase 2 (CaMKK2) and the androgen receptor in prostate cancer progression.

The androgen receptor (AR) plays a critical role in prostate cancer (PCa) progression, however, the molecular mechanisms by which the AR regulates cell proliferation in androgen-dependent and castration-resistant PCa are incompletely understood. We report that Ca(2+)/calmodulin-dependent kinase kinase 2 (CaMKK2) expression increases and becomes nuclear or perinuclear in advanced PCa. In the TRAMP (transgenic adenocarcinoma of mouse prostate) model of PCa, CaMKK2 expression increases with PCa progression with many cells exhibiting nuclear staining. CaMKK2 expression is higher in human castration-resistant tumor xenografts compared with androgen-responsive xenografts and is markedly higher in the AR-expressing, tumorigenic cell line LNCaP compared with cell lines that are AR-nonexpressing and/or nontumorigenic. In LNCaP cells, dihydrotestosterone induced CaMKK2 mRNA and protein expression and translocation of CaMKK2 to the nucleus. Conversely, androgen withdrawal suppressed CaMKK2 expression. Knockdown of CaMKK2 expression by RNAi reduced LNCaP cell proliferation and increased percentages of cells in G(1) phase, whereas correspondingly reducing percentages in S phase, of the cell cycle. CaMKK2 knockdown reduced expression of the AR target gene prostate-specific antigen at both mRNA and protein levels, AR transcriptional activity driven by androgen responsive elements from the prostate-specific probasin gene promoter and levels of the AR-regulated cell cycle proteins, cyclin D1 and hyperphosphorylated Rb. Our results suggest that in PCa progression, CaMKK2 and the AR are in a feedback loop in which CaMKK2 is induced by the AR to maintain AR activity, AR-dependent cell cycle control, and continued cell proliferation.