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At least 19 records

A Melanoma Brain Metastasis CTC Signature and CTC:B-cell Clusters Associate with Secondary Liver Metastasis: A Melanoma Brain–Liver Metastasis Axis

Melanoma brain metastasis is linked to dismal prognosis and low overall survival and is detected in up to 80% of patients at autopsy. Circulating tumor cells (CTC) are the smallest functional units of cancer and precursors of fatal metastasis. We previously used an unbiased multilevel approach to discover a unique ribosomal protein large/small subunit (RPL/RPS) CTC gene signature associated with melanoma brain metastasis. In this study, we hypothesized that CTC-driven melanoma brain metastasis secondary metastasis (“metastasis of metastasis” per clinical scenarios) has targeted organ specificity for the liver. We injected parallel cohorts of immunodeficient and newly developed humanized NBSGW (huNBSGW) mice with cells from CTC-derived melanoma brain metastasis to identify secondary metastatic patterns. We found the presence of a melanoma brain–liver metastasis axis in huNBSGW mice. Furthermore, RNA sequencing analysis of tissues showed a significant upregulation of the RPL/RPS CTC gene signature linked to metastatic spread to the liver. Additional RNA sequencing of CTCs from huNBSGW blood revealed extensive CTC clustering with human B cells in these mice. CTC:B-cell clusters were also upregulated in the blood of patients with primary melanoma and maintained either in CTC-driven melanoma brain metastasis or melanoma brain metastasis CTC–derived cells promoting liver metastasis. CTC-generated tumor tissues were interrogated at single-cell gene and protein expression levels (10x Genomics Xenium and HALO spatial biology platforms, respectively). Collectively, our findings suggest that heterotypic CTC:B-cell interactions can be critical at multiple stages of metastasis.

60 APPLIED LIFE SCIENCES↗

Sex Differences in Odds of Brain Metastasis and Outcomes by Brain Metastasis Status after Advanced Melanoma Diagnosis

Sex differences in cancer are well-established. However, less is known about sex differences in diagnosis of brain metastasis and outcomes among patients with advanced melanoma. Using a United States nationwide electronic health record-derived de-identified database, we evaluated patients diagnosed with advanced melanoma from 1 January 2011–30 July 2022 who received an oncologist-defined rule-based first line of therapy (n = 7969, 33% female according to EHR, 35% w/documentation of brain metastases). The odds of documented brain metastasis diagnosis were calculated using multivariable logistic regression adjusted for age, practice type, diagnosis period (pre/post-2017), ECOG performance status, anatomic site of melanoma, group stage, documentation of non-brain metastases prior to first-line of treatment, and BRAF positive status. Real-world overall survival (rwOS) and progression-free survival (rwPFS) starting from first-line initiation were assessed by sex, accounting for brain metastasis diagnosis as a time-varying covariate using the Cox proportional hazards model, with the same adjustments as the logistic model, excluding group stage, while also adjusting for race, socioeconomic status, and insurance status. Adjusted analysis revealed males with advanced melanoma were 22% more likely to receive a brain metastasis diagnosis compared to females (adjusted odds ratio [aOR]: 1.22, 95% confidence interval [CI]: 1.09, 1.36). Males with brain metastases had worse rwOS (aHR: 1.15, 95% CI: 1.04, 1.28) but not worse rwPFS (adjusted hazard ratio [aHR]: 1.04, 95% CI: 0.95, 1.14) following first-line treatment initiation. Among patients with advanced melanoma who were not diagnosed with brain metastases, survival was not different by sex (rwOS aHR: 1.06 [95% CI: 0.97, 1.16], rwPFS aHR: 1.02 [95% CI: 0.94, 1.1]). This study showed that males had greater odds of brain metastasis and, among those with brain metastasis, poorer rwOS compared to females, while there were no sex differences in clinical outcomes for those with advanced melanoma without brain metastasis.

60 APPLIED LIFE SCIENCES↗

A susceptibility gene signature for ERBB2-driven mammary tumour development and metastasis in collaborative cross mice

Background: Deeper insights into ERBB2-driven cancers are essential to develop new treatment approaches for ERBB2+ breast cancers (BCs). We employed the Collaborative Cross (CC) mouse model to unearth genetic factors underpinning Erbb2-driven mammary tumour development and metastasis. Methods: 732 F1 hybrid female mice between FVB/N MMTV-Erbb2 and 30 CC strains were monitored for mammary tumour phenotypes. GWAS pinpointed SNPs that influence various tumour phenotypes. Multivariate analyses and models were used to construct the polygenic score and to develop a mouse tumour susceptibility gene signature (mTSGS), where the corresponding human ortholog was identified and designated as hTSGS. The importance and clinical value of hTSGS in human BC was evaluated using public datasets, encompassing TCGA, METABRIC, GSE96058, and I-SPY2 cohorts. The predictive power of mTSGS for response to chemotherapy was validated in vivo using genetically diverse MMTV-Erbb2 mice. Findings: Distinct variances in tumour onset, multiplicity, and metastatic patterns were observed in F1-hybrid female mice between FVB/N MMTV-Erbb2 and 30 CC strains. Besides lung metastasis, liver and kidney metastases emerged in specific CC strains. GWAS identified specific SNPs significantly associated with tumour onset, multiplicity, lung metastasis, and liver metastasis. Multivariate analyses flagged SNPs in 20 genes (Stx6, Ramp1, Traf3ip1, Nckap5, Pfkfb2, Trmt1l, Rprd1b, Rer1, Sepsecs, Rhobtb1, Tsen15, Abcc3, Arid5b, Tnr, Dock2, Tti1, Fam81a, Oxr1, Plxna2, and Tbc1d31) independently tied to various tumour characteristics, designated as a mTSGS. hTSGS scores (hTSGSS) based on their transcriptional level showed prognostic values, superseding clinical factors and PAM50 subtype across multiple human BC cohorts, and predicted pathological complete response independent of and superior to MammaPrint score in I-SPY2 study. The power of mTSGS score for predicting chemotherapy response was further validated in an in vivo mouse MMTV-Erbb2 model, showing that, like findings in human patients, mouse tumours with low mTSGS scores were most likely to respond to treatment. Interpretation: Our investigation has unveiled many new genes predisposing individuals to ERBB2-driven cancer. Translational findings indicate that hTSGS holds promise as a biomarker for refining treatment strategies for patients with BC.

60 APPLIED LIFE SCIENCES↗

Computational ranking identifies Plexin-B2 in circulating tumor cell clustering with monocytes in breast cancer metastasis

Abstract Multicellular circulating tumor cell (CTC) clusters can be up to 50 times more efficient than single CTCs in mediating viable metastasis. Here, combining computational ranking and functional determination, we identify the transmembrane protein Plexin-B2 (PLXNB2) as one of the top molecular targets associated with unfavorable distant metastasis-free survival, showing enriched expression in CTC clusters versus single CTCs from patients with advanced breast cancer (mostly female). Loss of PLXNB2 (Plxnb2) reduces the formation of homotypic tumor cell clusters and heterotypic tumor-myeloid cell clusters, reducing spontaneous metastases in female mice bearing human (mouse) breast cancer. Interactions of PLXNB2 with its ligands SEMA4C on tumor cells and SEMA4A on myeloid cells (monocytes) promote homotypic and heterotypic CTC cluster formation, respectively, thereby driving lung metastasis. Global proteomic analysis reveals downstream effectors of the PLXNB2 pathway associated with tumor cell clustering. Thus, PLXNB2 is a therapeutic target for preventing new metastasis in breast cancer.

Science & Technology - Other Topics↗

Large-scale deep learning for metastasis detection in pathology reports

Objectives No existing algorithm can reliably identify metastasis from pathology reports across multiple cancer types and the entire US population. In this study, we develop a deep learning model that automatically detects patients with metastatic cancer by using pathology reports from many laboratories and of multiple cancer types. Materials and Methods We use 60 471 unstructured pathology reports from 4 Surveillance, Epidemiology, and End Results (SEER) registries. The reports were coded into 1 of 3 labels: metastasis negative, metastases positive, or metastasis undetermined. We utilize a task-specific deep neural network trained from scratch and compare its performance with a widely used large language model (LLM). Results Our deep learning architecture trained on task-specific data outperforms a general-purpose LLM, with a recall of 0.894 compared to 0.824. We quantified model uncertainty and used it to defer reports for human review. We found that retaining 72.9% of reports increased recall from 0.894 to 0.969. Discussion A smaller deep learning architecture trained on task-specific data outperforms a general LLM. Equally critical to model performance is the incorporation of uncertainty quantification, achieved here through an abstention mechanism. Conclusions This study’s finding demonstrate the feasibility of developing algorithms to automatically identify metastatic cancer cases from unstructured pathology reports.

machine learning↗

Formin‐like 2 promotes angiogenesis and metastasis of colorectal cancer by regulating the EGFL6 / CKAP4 / ERK axis

Abstract Increasing evidence indicates that angiogenesis plays a pivotal role in tumor progression. Formin‐like 2 (FMNL2) is well‐known for promoting metastasis; however, the molecular mechanisms by which FMNL2 promotes angiogenesis in colorectal cancer (CRC) remain unclear. Here, we found that FMNL2 promotes angiogenesis and metastasis of CRC in vitro and in vivo. The GDB/FH3 domain of FMNL2 directly interacts with epidermal growth factor‐like protein 6 (EGFL6). Formin‐like 2 promotes EGFL6 paracrine signaling by exosomes to regulate angiogenesis in CRC. Cytoskeleton associated protein 4 (CKAP4) is a downstream target of EGFL6 and is involved in CRC angiogenesis. Epidermal growth factor‐like protein 6 binds to the N‐terminus of CKAP4 to promote the migration of HUVECs by activating the ERK/MMP pathway. These findings suggest that FMNL2 promotes the migration of HUVECs and enhances angiogenesis and tumorigenesis in CRC by regulating the EGFL6/CKAP4/ERK axis. Therefore, the EGFL6/CKAP4/ERK axis could be a candidate therapeutic target for CRC treatment.

He, Guoyang↗

Comparative Uptake Patterns of Radioactive Iodine and [18F]-Fluorodeoxyglucose (FDG) in Metastatic Differentiated Thyroid Cancers

Background: Metastatic differentiated thyroid cancer (DTC) represents a molecularly heterogeneous group of cancers with varying radioactive iodine (RAI) and [ 18 F]-fluorodeoxyglucose (FDG) uptake patterns potentially correlated with the degree of de-differentiation through the so-called “flip-flop” phenomenon. However, it is unknown if RAI and FDG uptake patterns correlate with molecular status or metastatic site. Materials and Methods: A retrospective analysis of metastatic DTC patients (n = 46) with radioactive 131-iodine whole body scan (WBS) and FDG-PET imaging between 2008 and 2022 was performed. The inclusion criteria included accessible FDG-PET and WBS studies within 1 year of each other. Studies were interpreted by two blinded radiologists for iodine or FDG uptake in extrathyroidal sites including lungs, lymph nodes, and bone. Cases were stratified by BRAF V600E mutation status, histology, and a combination of tumor genotype and histology. The data were analyzed by McNemar’s Chi-square test. Results: Lung metastasis FDG uptake was significantly more common than iodine uptake (WBS: 52%, FDG: 84%, p = 0.04), but no significant differences were found for lymph or bone metastases. Lung metastasis FDG uptake was significantly more prevalent in the papillary pattern sub-cohort (WBS: 37%, FDG: 89%, p = 0.02) than the follicular pattern sub-cohort (WBS: 75%, FDG: 75%, p = 1.00). Similarly, BRAF V600E+ tumors with lung metastases also demonstrated a preponderance of FDG uptake (WBS: 29%, FDG: 93%, p = 0.02) than BRAF V600E- tumors (WBS: 83%, FDG: 83%, p = 1.00) with lung metastases. Papillary histology featured higher FDG uptake in lung metastasis (WBS: 39%, FDG: 89%, p = 0.03) compared with follicular histology (WBS: 69%, FDG: 77%, p = 1.00). Patients with papillary pattern disease, BRAF V600E+ mutation, or papillary histology had reduced agreement between both modalities in uptake at all metastatic sites compared with those with follicular pattern disease, BRAF V600E- mutation, or follicular histology. Low agreement in lymph node uptake was observed in all patients irrespective of molecular status or histology. Conclusions: The pattern of FDG-PET and radioiodine uptake is dependent on molecular status and metastatic site, with those with papillary histology or BRAF V600E+ mutation featuring increased FDG uptake in distant metastasis. Further study with an expanded cohort may identify which patients may benefit from specific imaging modalities to recognize and surveil metastases.

60 APPLIED LIFE SCIENCES↗

Machine learning-assisted elucidation of CD81–CD44 interactions in promoting cancer stemness and extracellular vesicle integrity

Tumor-initiating cells with reprogramming plasticity or stem-progenitor cell properties (stemness) are thought to be essential for cancer development and metastatic regeneration in many cancers; however, elucidation of the underlying molecular network and pathways remains demanding. Combining machine learning and experimental investigation, here we report CD81, a tetraspanin transmembrane protein known to be enriched in extracellular vesicles (EVs), as a newly identified driver of breast cancer stemness and metastasis. Using protein structure modeling and interface prediction-guided mutagenesis, we demonstrate that membrane CD81 interacts with CD44 through their extracellular regions in promoting tumor cell cluster formation and lung metastasis of triple negative breast cancer (TNBC) in human and mouse models. In-depth global and phosphoproteomic analyses of tumor cells deficient with CD81 or CD44 unveils endocytosis-related pathway alterations, leading to further identification of a quality-keeping role of CD44 and CD81 in EV secretion as well as in EV-associated stemness-promoting function. CD81 is coexpressed along with CD44 in human circulating tumor cells (CTCs) and enriched in clustered CTCs that promote cancer stemness and metastasis, supporting the clinical significance of CD81 in association with patient outcomes. Our study highlights machine learning as a powerful tool in facilitating the molecular understanding of new molecular targets in regulating stemness and metastasis of TNBC.

59 BASIC BIOLOGICAL SCIENCES↗

Integrated structural model of the palladin–actin complex using XL ‐ MS , docking, NMR , and SAXS

Abstract Palladin is an actin‐binding protein that accelerates actin polymerization and is linked to the metastasis of several types of cancer. Previously, three lysine residues in an immunoglobulin‐like domain of palladin have been identified as essential for actin binding. However, it is still unknown where palladin binds to F‐actin. Evidence that palladin binds to the sides of actin filaments to facilitate branching is supported by our previous study showing that palladin was able to compensate for Arp2/3 in the formation of Listeria actin comet tails. Here, we used chemical crosslinking to covalently link palladin and F‐actin residues based on spatial proximity. Samples were then enzymatically digested, separated by liquid chromatography, and analyzed by tandem mass spectrometry. Peptides containing the crosslinks and specific residues involved were then identified for input to the HADDOCK docking server to model the most likely binding conformation. Small‐angle x‐ray scattering was used to provide further insight into palladin flexibility and the binding interface, and NMR spectra identified potential interactions between palladin's Ig domains. Our final structural model of the F‐actin:palladin complex revealed how palladin interacts with and stabilizes F‐actin at the interface between two actin monomers. Three actin residues that were identified in this study also appear commonly in the actin‐binding interface with other proteins such as myotilin, myosin, and tropomodulin. An accurate structural representation of the complex between palladin and actin extends our understanding of palladin's role in promoting cancer metastasis through the regulation of actin dynamics.

Sargent, Rachel [Department of Chemistry and Bioch↗

Investigating the FLASH Effect in a Rat Brain Organotypic Model With a Novel High-Energy Electron Beam

Ultrahigh dose rate (FLASH) radiation therapy is reported to reduce normal tissue toxicity while maintaining tumor control; however, mechanism(s) remain obscure. To study FLASH mechanisms in brain tissue, we developed a novel experimental platform featuring a specialized high-energy electron linear accelerator, High Intensity Gamma Ray Source (HIGS), paired with an organotypic ex vivo brain metastasis model. We varied interpulse spacing to modulate the mean dose rate (MDR) of our unique 35 MeV electron beam, while maintaining extremely high instantaneous dose rate (IDR). We characterized dosimetry and targeting accuracy of the FLASH beam with film dosimetry. We combined this FLASH beam with an organotypic rat brain slice/breast carcinoma coculture model of brain metastasis to assess effects on normal and neoplastic tissues. Live-cell and bioluminescence imaging demonstrated cancer cell growth effects, whereas normal tissue responses and immune activation were assessed using live-cell imaging, cytokine profiles, and confocal microscopy. Here, we performed comparison experiments with 20 MeV electrons from a Varian clinical linear accelerator (VCLA) using conventional dose rates. The highest IDR of the FLASH beam to date was 20.7 ± 0.6 MGy/s, with maximum MDR of 20.7 MGy/s delivered in 1 pulse of 1 µs duration. Beam targeting was accurate to <1 mm and reproducible. HIGS-FLASH and VCLA dose rates equivalently decreased cancer cell growth. HIGS-FLASH irradiation significantly increased tumor necrosis factor α and fractalkine levels and confocal microscopy revealed distinct changes in microglial morphology slices suggesting microglia activation. Our novel experimental platform produces extremely high dose rates and rapid normal/neoplastic tissue readouts for mechanistic research into the effects of FLASH radiation in the brain. HIGS-FLASH irradiation induces comparable cancer cell growth inhibition but differential effects on cytokines and microglial morphology, suggesting that acute innate immune responses may be involved in FLASH normal tissue effects in the brain.

Kay, Tyler V. [Duke University, Durham, NC (United↗

Targeting prostate tumor low–molecular weight tyrosine phosphatase for oxidation-sensitizing therapy

Protein tyrosine phosphatases (PTPs) play major roles in cancer and are emerging as therapeutic targets. Recent reports suggest low–molecular weight PTP (LMPTP)—encoded by the ACP1 gene—is overexpressed in prostate tumors. We found ACP1 up-regulated in human prostate tumors and ACP1 expression inversely correlated with overall survival. Using CRISPR-Cas9–generated LMPTP knockout C4-2B and MyC-CaP cells, we identified LMPTP as a critical promoter of prostate cancer (PCa) growth and bone metastasis. Through metabolomics, we found that LMPTP promotes PCa cell glutathione synthesis by dephosphorylating glutathione synthetase on inhibitory Tyr 270 . PCa cells lacking LMPTP showed reduced glutathione, enhanced activation of eukaryotic initiation factor 2–mediated stress response, and enhanced reactive oxygen species after exposure to taxane drugs. LMPTP inhibition slowed primary and bone metastatic prostate tumor growth in mice. These findings reveal a role for LMPTP as a critical promoter of PCa growth and metastasis and validate LMPTP inhibition as a therapeutic strategy for treating PCa through sensitization to oxidative stress.

60 APPLIED LIFE SCIENCES↗

The FBXW7-binding sites on FAM83D are potential targets for cancer therapy

Increasing evidence shows the oncogenic function of FAM83D in human cancer, but how FAM83D exerts its oncogenic function remains largely unclear. Here, we investigated the importance of FAM83D/FBXW7 interaction in breast cancer (BC). We systematically mapped the FBXW7-binding sites on FAM83D through a comprehensive mutational analysis together with co-immunoprecipitation assay. Mutations at the FBXW7-binding sites on FAM83D led to that FAM83D lost its capability to promote the ubiquitination and proteasomal degradation of FBXW7; cell proliferation, migration, and invasion in vitro; and tumor growth and metastasis in vivo, indicating that the FBXW7-binding sites on FAM83D are essential for its oncogenic functions. A meta-evaluation of FAM83D revealed that the prognostic impact of FAM83D was independent on molecular subtypes. The higher expression of FAM83D has poorer prognosis. Moreover, high expression of FAM83D confers resistance to chemotherapy in BCs, which is experimentally validated in vitro. We conclude that identification of FBXW7-binding sites on FAM83D not only reveals the importance for FAM83D oncogenic function, but also provides valuable insights for drug target.

60 APPLIED LIFE SCIENCES↗

LncRNA ZFAS1 promotes invasion of medullary thyroid carcinoma by enhancing EPAS1 expression via miR‐214‐3p/UCHL1 axis

Abstract lncRNA ZFAS1 was identified to facilitate thyroid cancer, but its role in medullary thyroid carcinoma (MTC) remains unknown. This study aimed to unravel the potential function of this lncRNA in MTC by investigating the involvement of the lncRNA ZFAS1 in a ceRNA network that regulates MTC invasion. Proliferation, invasion, and migration of cells were evaluated using EdU staining and Transwell assays. Immunoprecipitation (IP) assays, dual‐fluorescence reporter, and RNA IP assays were employed to examine the binding interaction among genes. Nude mice were used to explore the role of lncRNA ZFAS1 in MTC in vivo. ZFAS1 and EPAS1 were upregulated in MTC. Silencing ZFAS1 inhibited MTC cell proliferation and invasion under hypoxic conditions, which reduced EPAS1 protein levels. UCHL1 knockdown increased EPAS1 ubiquitination. ZFAS1 positively regulated UCHL1 expression by binding to miR‐214‐3p. Finally, silencing ZFAS1 significantly repressed tumor formation and metastasis in MTC. LncRNA ZFAS1 promotes invasion of MTC by upregulating EPAS1 expression via the miR‐214‐3p/UCHL1 axis.

Chen, Wenjing↗

Targeted inhibition of MASTL kinase activity induces apoptosis in breast cancer

Microtubule-associated serine/threonine kinase-like (MASTL) (or Greatwall kinase (GWL)) is an important cell cycle regulating kinase that regulates the G2-M transition. Uncontrolled MASTL activity is implicated in breast cancer progression. To date, very few inhibitors have been reported against this protein. Here, structure-based computational modeling indicates that the natural product flavopiridol (FLV) binds strongly to MASTL and these results are validated using molecular dynamics simulation studies. Further, an in vitro kinase assay reveals an EC 50 (effective concentration) value of FLV to be 82.1 nM and a better IC 50 compared to the positive reference compound, staurosporine. FLV is found to inhibit MASTL kinase activity, arresting the cell growth in the G1 phase and inducing apoptosis in breast cancer cells. Consistent with these results differential gene expression obtained using RNA sequencing studies, and validated by RT PCR and immunoblot analysis, indicate that MASTL inhibition induces cell cycle arrest and apoptotic-related genes. Furthermore, metastasis- and inflammation- related genes are downregulated. Thus, the deregulation of MASTL signaling pathways on targeted inhibition of its kinase activity is revealed. This study lays a strong foundation for investigating FLV as a lead compound in breast cancer therapeutics.

60 APPLIED LIFE SCIENCES↗

A multiscale model of immune surveillance in micrometastases gives insights on cancer patient digital twins

Abstract Metastasis is the leading cause of death in patients with cancer, driving considerable scientific and clinical interest in immunosurveillance of micrometastases. We investigated this process by creating a multiscale mathematical model to study the interactions between the immune system and the progression of micrometastases in general epithelial tissue. We analyzed the parameter space of the model using high-throughput computing resources to generate over 100,000 virtual patient trajectories. We demonstrated that the model could recapitulate a wide variety of virtual patient trajectories, including uncontrolled growth, partial response, and complete immune response to tumor growth. We classified the virtual patients and identified key patient parameters with the greatest effect on the simulated immunosurveillance. We highlight the lessons derived from this analysis and their impact on the nascent field of cancer patient digital twins (CPDTs). While CPDTs could enable clinicians to systematically dissect the complexity of cancer in each individual patient and inform treatment choices, our work shows that key challenges remain before we can reach this vision. In particular, we show that there remain considerable uncertainties in immune responses, unreliable patient stratification, and unpredictable personalized treatment. Nonetheless, we also show that in spite of these challenges, patient-specific models suggest strategies to increase control of clinically undetectable micrometastases even without complete parameter certainty.

Mathematical & Computational Biology↗