Biology subjects

Ortiz, M.

Publications and source records attributed to Ortiz, M..

At least 19 recordsLinked to original sources

bioRxiv2026

Tumor-derived FXII engages the intrinsic coagulation cascade to support breast cancer liver metastasis.

Metastasis is the leading cause of death in breast cancer, yet the mechanisms controlling organotropism are not well defined. Coagulation has emerged as a biologically relevant contributor to metastatic progression, but mechanisms linking pro-thrombotic phenotypes to organ-specific metastasis remain unresolved, significantly hindering the development of novel treatments. Here, a serial transplantation approach was used to enrich for liver organotropism from a spontaneous mouse mammary tumor model with occasional liver and lymph node metastasis. Comparative transcriptomics between the enriched liver and lymph node metastases revealed strong upregulation of coagulation in liver metastases, due in part to loss of repression of FXII with knockout of the E2F5 transcription factor. In vitro clotting assays demonstrated that tumor-derived FXII was sufficient to induce fibrin(ogen) clot formation. Moreover, liver metastatic cells exhibit elevated lipid peroxide levels and impaired lipid droplet formation associated with a pro-coagulant phenotype. Inhibition of coagulation with low molecular weight heparin reduced the presence of circulating tumor cells and suppressed liver metastasis in the mouse model. Human electronic health record data supported the translational relevance of these findings. Together, these data reveal a new mouse model where loss of E2F5 has resulted in tumors with elevated expression of FXII that have a propensity for liver metastasis and illustrates that anti-coagulation dramatically reduces the liver-specific metastasis in breast cancer. HighlightsE2F5 conditional knockout model develops breast tumors with liver tropism Liver metastasis hijacks the intrinsic coagulation cascade mediated by tumor-derived FXII Liver metastatic cells displayed lipid metabolic alterations that contributed to a pro-coagulant phenotype Low molecular weight heparin blocks liver metastasis and significantly reduces circulating tumor cells

cancer biology↗

bioRxiv2026

Tumor Protein D54 (TPD54) regulates intracellular protein trafficking, cellular function and disease progression in melanoma

To facilitate survival, migration and evasion of immune surveillance, cancer cells tightly coordinate the synthesis and trafficking of a diverse repertoire of proteins to their cell surface and the surrounding tumor microenvironment. A key mechanism underlying this process is the intracellular membrane trafficking pathways, including vesicular transport systems. There remains a paucity of mechanistic insight into the regulatory components that mediate nascent protein trafficking and their dysregulation in cancer. Herein, we investigate Tumor Protein D54 (TPD54) as a central regulator of intracellular protein transport that is exploited by melanoma cells to promote disease progression. Integrative analyses of patient-derived tumor tissue specimens show that the expression of TPD52L2 (the gene encoding TPD54) is frequently overexpressed in melanoma and correlates with adverse clinical outcomes, including reduced responses to immune checkpoint blockade. Mechanistic investigations further revealed that TPD54 maintains Golgi integrity and orchestrates trafficking of early endosomes, anterograde vesicles and extracellular vesicles. Functionally, TPD54 augments the secretion of pro-cancerous cytokines, increases the cell surface expression of adhesion-signaling receptors (e.g. integrin-{beta}1 and desmoglein-2), promotes melanoma cell migration and elevates their capability to undergo vasculogenic mimicry. Targeting TPD52L2 in two mouse models of melanoma (B16-F10 and HCmel12) showed significant attenuation of tumor growth, disrupted tumor vasculature, enhanced anti-tumor immunity with infiltration of CD8+ T cells and reduced metastatic disease. Collectively, these findings establish TPD54 as a critical and previously underappreciated regulator of protein trafficking in cancer cells that directly contributes to disease progression and highlights its potential as a novel therapeutic target to combat melanoma.

cancer biology↗

bioRxiv2026

Environmental Gradients Shape the Hydrocarbon-Degrading Microbiome in Two Mid Atlantic Bays.

Hydrocarbons are recalcitrant organic matter that are released into the environment via natural and anthropogenic activities. We hypothesized that abiotic and biotic factors, including salinity, temperature, seasonality, microbial interactions, and functional redundancy, influence the abundance and activity of potential hydrocarbon degraders in the Delaware and Chesapeake Bays. We identified key genes in hydrocarbon degradation pathways in metagenomes, metatranscriptomes, and metagenome assembled genomes (MAGs) from these estuaries. Aerobic aromatic and alkane degradation pathways predominated in both estuaries, with higher gene abundances observed in low-salinity spring and summer samples. Hydrocarbon degrading MAG abundance were significantly structured by salinity, temperature, nitrate, and silicate concentrations. Metatranscriptomic analyses revealed consistently higher expression of aerobic alkane and aromatic degradation genes in the Delaware compared to the Chesapeake Bay, with the highest occurring under low-salinity spring conditions in the former. Catechol degradation pathways exhibited high functional redundancy, whereas the naphthalene degradation pathway showed restricted distribution. Co-expression analysis revealed that Burkholderiales displayed condition dependent metabolic coupling while Pseudomonadales integrated hydrocarbon degradation with fermentation and central metabolism, demonstrating complementary strategies that support multi-scale ecosystem resilience. In conclusion, environmental gradients and taxon-specific metabolic strategies together govern hydrocarbon degradation potential in these estuaries, with implications for predicting ecosystem responses to hydrocarbon inputs under changing conditions. ImportanceCoastal estuaries are among the most contaminated aquatic environments on Earth, receiving continuous hydrocarbon inputs from industrial activity, urban runoff, and natural sources. Microorganisms are the primary agents of hydrocarbon breakdown in these systems yet predicting when and where this capacity is active and how resilient it is to environmental change remains a major challenge. Using paired genomic and transcriptomic data from microbial genomes across two major mid-Atlantic estuaries, we show that hydrocarbon degradation capacity is not uniformly distributed but is instead shaped by salinity, nutrients, and seasonality in pathway-specific ways. Critically, dominant degrader taxa employ fundamentally different metabolic strategies to sustain this function across fluctuating conditions, providing a form of community-level insurance against environmental disturbance. These findings advance our ability to predict microbial hydrocarbon degradation in coastal systems and inform nature-based approaches to bioremediation under increasing climate and anthropogenic pressures.

genomics↗

bioRxiv2025

Eph-Ephrin Tetramerization Inhibitors Target Bidirectional Signaling to Combat Pain and Addiction

Eph receptors and Ephrin ligands are a large highly conserved family of interacting membrane-anchored molecules that form dimers, tetramers, and tetramer superclusters to become activated and signal upon cell-cell contact. While most noted for their ability to transduce bidirectional phosphotyrosine signals in development, certain Ephs and Ephrins also become overexpressed and participate in pathological situations, including EphB1 in chronic pain/addiction and EphB2 in fibroinflammatory disorders and cancer. We searched for small molecules that disrupt EphB-EphrinB receptor-ligand interactions and discovered compounds with submicromolar activity that specifically inhibit formation of the tetramer. Compounds effectively target tetramer-driven EphB1-EphrinB2 and EphB2-EphrinB2 interactions, while showing less action towards the more dimer-driven EphB4-EphrinB2 interaction. They are orally available, exhibit drug-like qualities to reduce both EphB forward and EphrinB reverse signaling, and act to blunt inflammatory pain and opioid withdrawal behaviors. Tetramer inhibitors thus present a novel way to target Eph-Ephrin macromolecular interactions and counter pathologies caused or exacerbated by excessive bidirectional signaling.

molecular biology↗

bioRxiv2025

A long non-coding RNA regulates triazole antifungal susceptibility and virulence in Aspergillus fumigatus

Azole-resistant Aspergillus infections are a source of increasing concern with limited alternative therapeutic options. However, as most infections are still caused by azole-susceptible Aspergillus strains, there is a need to better understand fungal responses to azole antifungals. To this end, we discover that a long non-coding RNA, afu-182, is a major regulator of cyp51-independent sub-MIC azole response. We observe that loss of afu-182 leads to increased surface attached growth and poor treated disease outcomes in a murine model of invasive pulmonary aspergillosis upon azole treatment. In contrast, overexpression of afu-182 significantly reduces fungal burden in animals treated with the azole drug, posaconazole. Importantly, afu-182 levels decrease upon azole exposure and in an azole adaptation experiment, continuous exposure to low dose azole led to MIC increase in an afu-182 dependent manner. Whole transcriptome analyses revealed that azole drug treatment leads to an increase in transcripts of genes encoding 7-transmembrane domain proteins of the RTA1 family, and these proteins are negatively regulated by afu-182. Two RTA1 family genes have individual and combined effects and are sufficient to increase fungal susceptibility to azole drugs in the WT strain. Taken together, our data show a role of the long non-coding RNA afu-182 in regulating Aspergillus fumigatus response to azole drugs both in vitro and in vivo. ImportanceDrug resistance in Aspergillus is a major challenge that is often associated with the agricultural use of azoles in the environment. How drug resistance arises in vivo is still an active area of research. Here, we show that azole exposure results in fungal adaptation by lowering the RNA levels of lncRNA, which upon low dose azole exposure leads to an increase in azole drug MIC.

molecular biology↗

bioRxiv2025

Decoding human placental cellular and molecular responses to maternal obesity and fetal growth

Maternal obesity increases risk of large-for-gestational-age (LGA) births and subsequent cardiometabolic disorders in offspring. To identify placental signatures associated with these outcomes, we performed single-nucleus RNAseq on placentas from women with obesity delivering appropriate-for-gestational-age (AGA) or LGA infants, compared to normal-weight controls. In maternal obesity, regardless of fetal growth, syncytiotrophoblasts showed upregulated hypoxia and TNF- signaling, while cytotrophoblasts exhibited downregulated receptor tyrosine kinase signaling. However, only in LGA placentas, villous non-trophoblasts displayed upregulated TNF- signaling and inflammatory responses. Notably, Hofbauer cells in LGA placentas presented transcriptional alterations in immunometabolism-related genes and functioned as main signaling senders via SPP1. Importantly, we recapitulated syncytiotrophoblast responses to maternal obesity using a novel microfluidic organoids-on-a-chip co-culture. These findings reveal distinct transcriptional responses of placental cell types to maternal obesity and fetal growth, highlighting potential intervention pathways to mitigate future disease risks.

developmental biology↗

bioRxiv2023

Integrative multi-omic sequencing reveals the MMTV-Myc mouse model mimics human breast cancer heterogeneity

BackgroundBreast cancer is a complex and heterogeneous disease with distinct subtypes and molecular profiles corresponding to different clinical outcomes. Mouse models of breast cancer are widely used, but their relevance in capturing the heterogeneity of human disease is unclear. Previous studies have shown the heterogeneity at the gene expression level for the MMTV-Myc model, but have only speculated on the underlying genetics. ResultsHerein, we examine three common histological subtypes of the MMTV-Myc model through whole genome sequencing and have integrated these results with gene expression data. Significantly, key genomic alterations driving cell signaling pathways were well conserved within histological subtypes. Genomic changes included frequent, co-occurring mutations in KIT and RARA in the microacinar histological subtype as well as SCRIB mutations in the EMT subtype. EMT tumors additionally displayed strong KRAS activation signatures downstream of genetic activating events primarily ascribed to KRAS activating mutations, but also FGFR2 amplification. Analogous genetic events in human breast cancer showed stark decreases in overall survival. In further analyzing transcriptional heterogeneity of the MMTV-Myc model, we report a supervised machine learning model that classifies MMTV-Myc histological subtypes and other mouse models as being representative of different human intrinsic breast cancer subtypes. ConclusionsWe conclude the well-established MMTV-Myc mouse model presents further opportunities for investigation of human breast cancer heterogeneity.

cancer biology↗

bioRxiv2023

ELITE: Expression deconvoLution using lInear optimizaTion in bulk transcriptomics mixturEs

Understanding the cellular composition of tissue samples is crucial for identifying the molecular mechanisms underlying diseases and developing cellular targets for therapeutic interventions. Digital cytometry methods have been developed to predict tissue composition from bulk transcriptomic data, avoiding the high cost associated with single-cell profiling. Here, we present ELITE, a new digital cytometry method that utilizes linear programming to solve the deconvolution problem. ELITE uses as inputs a mixture matrix representing bulk measurements, and a signature matrix representing molecular fingerprints of the cell types to be identified. The signature matrix can be obtained from single-cell datasets or the literature, making ELITE more flexible than other methods that rely solely on single-cell data. We evaluated ELITE on three publicly available single-cell datasets and compared it with five other deconvolution methods, showing superior performance, particularly when there were cell types with similar expression profiles. As a case study, we evaluated the prediction of tumor cellularity using purity estimates from 20 different TCGA carcinoma datasets.

bioinformatics↗

bioRxiv2022

Elimusertib outperforms standard of care chemotherapy in preclinical patient-derived pediatric solid tumor models

The small molecule inhibitor of ataxia telangiectasia and Rad3-related protein (ATR), elimusertib, is currently being tested clinically in various cancer entities in adults and children. Its preclinical anti-tumor activity in pediatric malignancies, however, is largely unknown. We here assessed the preclinical activity of elimusertib in >40 cell lines and >30 patient-derived xenograft (PDX) models derived from common pediatric solid tumor entities. Detailed in vitro and in vivo molecular characterization of the treated models enabled the evaluation of response biomarkers. Pronounced objective response rates were observed for elimusertib monotherapy in PDX, when treated with a regimen currently used in clinical trials. Strikingly, elimusertib outperformed standard of care chemotherapies, particularly in alveolar rhabdomysarcoma PDX. Thus, elimusertib has strong preclinical anti-tumor activity in pediatric solid tumor models, which may translate to clinically meaningful responses in patients. Statement of translational relevanceElimusertib is a small molecule inhibitor of ATR. ATR inhibitors have shown promising results as anticancer agents in adult cancers, but there is limited information on their effectiveness in pediatric solid tumors. Using a cohort of 32 patient-derived xenografts from pediatric solid tumors, we here evaluated the therapeutic potential of elimusertib in vivo. Elimusertib reduced tumor volume growth in all samples. Elimusertib had very limited toxicity and was potent even in tumors with preexisting chemoresistance. Our preclinical data indicates that elimusertib is a safe and potent therapeutic option for pediatric solid tumors. This data may serve as a rationale for the development of pediatric clinical trials for ATR inhibitors.

cancer biology↗

bioRxiv2022

A model-free Data-Driven paradigm for in situ patient-specific prediction of human brain response to ultrasound stimulation

We present a class of model-free Data-Driven solvers that effectively enable the utilization of in situ and in vivo imaging data directly in full-scale calculations of the mechanical response of the human brain to sonic and ultrasonic stimulation, entirely bypassing the need for analytical modeling or regression of the data. The well-posedness of the approach and its convergence with respect to data are proven analytically. We demonstrate the approach, including its ability to make detailed spatially-resolved patient-specific predictions of wave patterns, using public-domain MRI images, MRE data and commercially available solid-mechanics software.

biophysics↗

bioRxiv2022

Retinoic acid signaling modulation guides in vitro specification of human heart field-specific progenitor pools

Cardiogenesis relies on the precise spatiotemporal coordination of multiple progenitor populations. Understanding the specification and differentiation of these distinct progenitor pools during human embryonic development is crucial for advancing our knowledge of congenital cardiac malformations and designing new regenerative therapies. By combining genetic labelling, single-cell transcriptomics, and ex vivo human-mouse embryonic chimeras we uncovered that modulation of retinoic acid signaling instructs human pluripotent stem cells to form heart field-specific progenitors with distinct fate potentials. In addition to the classical first and second heart fields, we observed the appearance of juxta-cardiac field progenitors giving rise to both myocardial and epicardial cells. Applying these findings to stem-cell based disease modelling we identified specific transcriptional dysregulation in first and second heart field progenitors derived from stem cells of a patient with hypoplastic left heart syndrome. This highlights the suitability of our in vitro differentiation platform for studying human cardiac development and disease.

cell biology↗

bioRxiv2021

Mechanics Of Ultrasonic Neuromodulation In A Mouse Subject

Ultrasound neuromodulation (UNM), where a region in the brain is targeted by focused ultrasound (FUS), which, in turn, causes excitation or inhibition of neural activity, has recently received considerable attention as a promising tool for neuroscience. Despite its great potential, several aspects of UNM are still unknown. An important question pertains to the off-target sensory effects of UNM and their dependence on stimulation frequency. To understand these effects, we have developed a finite-element model of a mouse, including elasticity and viscoelasticity, and used it to interrogate the response of mouse models to focused ultrasound (FUS). We find that, while some degree of focusing and magnification of the signal is achieved within the brain, the induced pressure-wave pattern is complex and delocalized. In addition, we find that the brain is largely insulated, or cloaked, from shear waves by the cranium and that the shear waves are largely carried away from the skull by the vertebral column, which acts as a waveguide. We find that, as expected, this waveguide mechanism is strongly frequency dependent, which may contribute to the frequency dependence of UNM effects. Our calculations further suggest that off-target skin locations experience displacements and stresses at levels that, while greatly attenuated from the source, could nevertheless induce sensory responses in the subject.

neuroscience↗

bioRxiv2021

ELIMINATOR: Essentiality anaLysIs using MultIsystem Networks And inTeger prOgRamming

A gene is considered as essential when it is indispensable for cells to grow and replicate under a certain environment. However, gene essentiality is not a structural property but rather a contextual one, which depends on the specific biological conditions affecting the cell. This circumstantial essentiality of genes is what brings the attention of scientist since we can identify genes essential for cancer cells but not essential for healthy cells. This same contextuality makes their identification extremely challenging. Huge experimental efforts such as Project Achilles where the essentiality of thousands of genes is measured in over one thousand cell lines together with a plethora of molecular data (transcriptomics, copy number, mutations, etc.) can shed light on the causality behind the essentiality of a gene in a given environment by associating the measured essentiality to molecular features of the cell line. Here, we present an in-silico method for the identification of patient-specific essential genes using constraint-based modelling (CBM). Our method expands the ideas behind traditional CBM to accommodate multisystem networks, that is a biological network that focuses on complex interactions within several biological systems. In essence, it first calculates the minimum number of non-expressed genes required to be active by the cell to sustain life as defined by a set of requirements; and second, it performs an exhaustive in-silico gene knockout to find those that lead to the need of activating extra non-expressed genes. We validated the proposed methodology using a set of 452 cancer cell lines derived from the Cancer Cell Line Encyclopedia where an exhaustive experimental large-scale gene knockout study using CRISPR (Achilles Project) evaluates the impact of each removal. We also show that the integration of different essentiality predictions per gene, what we called Essentiality Congruity Score, (derived from multiple pathways) reduces the number of false positives. Finally, we explored the gene essentiality predictions for a breast cancer patient dataset, and our results showed high concordance with previous publications. These findings suggest that identifying genes whose activity are fundamental to sustain cellular life in a patient-specific manner is feasible using in-silico methods. The patient-level gene essentiality predictions can pave the way for precision medicine by identifying potential drug targets whose deletion can induce death in tumour cells.

bioinformatics↗

bioRxiv2021

TMPRSS2 structure-phylogeny repositions Avoralstat for SARS-CoV-2 prophylaxis in mice

Drugs targeting host proteins can act prophylactically to reduce viral burden early in disease and limit morbidity, even with antivirals and vaccination. Transmembrane serine protease 2 (TMPRSS2) is a human protease required for SARS-CoV-2 viral entry and may represent such a target.1-3 We hypothesized drugs selected from proteins related by their tertiary structure, rather than their primary structure, were likely to interact with TMPRSS2. We created a structure-based phylogenetic computational tool 3DPhyloFold to systematically identify structurally similar serine proteases with known therapeutic inhibitors and demonstrated effective inhibition of SARS-CoV-2 infection in vitro and in vivo.4,5 Several candidate compounds, Avoralstat, PCI-27483, Antipain, and Soybean-Trypsin-Inhibitor, inhibited TMPRSS2 in biochemical and cell infection assays. Avoralstat, a clinically tested Kallikrein-related B1 inhibitor,6 inhibited SARS-CoV-2 entry and replication in human airway epithelial cells. In an in vivo proof of principle,5 Avoralstat significantly reduced lung tissue titers and mitigated weight-loss when administered prophylactically to SARS-CoV-2 susceptible mice indicating its potential to be repositioned for COVID-19 prophylaxis in humans.

microbiology↗

bioRxiv2020

A genome compendium reveals diverse metabolic adaptations of Antarctic soil microorganisms

A surprising diversity and abundance of microorganisms resides in the cold desert soils of Antarctica. The metabolic processes that sustain them, however, are poorly understood. In this study, we used metagenomic and biogeochemical approaches to study the microbial communities in 16 physicochemically diverse mountainous and glacial soils from remote sites in South Victoria Land, north of the Mackay Glacier. We assembled 451 metagenome-assembled genomes from 18 bacterial and archaeal phyla, constituting the largest resource of Antarctic soil microbial genomes to date. The most abundant and prevalent microorganisms are metabolically versatile aerobes that use atmospheric hydrogen and carbon monoxide to meet energy, carbon, and, through metabolic water production, hydration needs. Phylogenetic analysis and structural modelling infer that bacteria from nine phyla can scavenge atmospheric hydrogen using a previously unreported enzyme family, the group 1l [NiFe]-hydrogenases. Consistently, gas chromatography measurements confirmed most soils rapidly consume atmospheric hydrogen and carbon monoxide, and provide the first experimental evidence of methane oxidation in non-maritime Antarctica. We also recovered genomes of microorganisms capable of oxidizing other inorganic compounds, including nitrogen, sulfur, and iron compounds, as well as harvesting solar energy via photosystems and novel microbial rhodopsins. Bacterial lineages defined by symbiotic lifestyles, including Patescibacteria, Chlamydiae, and predatory Bdellovibrionota, were also surprisingly abundant. We conclude that the dominant microorganisms in Antarctic soils adopt mixotrophic strategies for energy and sometimes carbon acquisition, though they co-exist with diverse bacteria and archaea that adopt more specialist lifestyles. These unprecedented insights and associated genome compendium will inform efforts to protect biodiversity in this continent.

microbiology↗

bioRxiv2020

Transcranial Focused Ultrasound Generates Skull-Conducted Shear Waves: Computational Model and Implications for Neuromodulation

Focused ultrasound (FUS) is an established technique for non-invasive surgery and has recently attracted considerable attention as a potential method for non-invasive neuromodulation. While the pressure waves generated by FUS in this context have been extensively studied, the accompanying shear waves are often neglected due to the relatively high shear compliance of soft tissues. However, in bony structures such as the skull, acoustic pressure can also induce significant shear waves that could propagate outside the ultrasound focus. Here, we investigate wave propagation in the human cranium by means of a finite-element model that accounts for the anatomy, elasticity and viscoelasticity of the skull and brain. We show that, when a region on the frontal lobe is subjected to FUS, the skull acts as a wave guide for shear waves, resulting in their propagation to off-target structures such as the cochlea. This effect helps explain the off-target auditory responses observed during neuromodulation experiments and informs the development of mitigation and sham control strategies.

biophysics↗

bioRxiv2019

Selective Ablation of Cancer Cells with Low Intensity Pulsed Ultrasound

Ultrasound can be focused into deep tissues with millimeter precision to perform non-invasive ablative therapy for diseases such as cancer. In most cases, this ablation uses high intensity ultrasound to deposit non-selective thermal or mechanical energy at the ultrasound focus, damaging both healthy bystander tissue and cancer cells. Here we describe an alternative low intensity pulsed ultrasound approach that leverages the distinct mechanical properties of neoplastic cells to achieve inherent cancer selectivity. We show that when applied at a specific frequency and pulse duration, focused ultrasound selectively disrupts a panel of breast, colon, and leukemia cancer cell models in suspension without significantly damaging healthy immune or red blood cells. Mechanistic experiments reveal that the formation of acoustic standing waves and the emergence of cell-seeded cavitation lead to cytoskeletal disruption, expression of apoptotic markers, and cell death. The inherent selectivity of this low intensity pulsed ultrasound approach offers a potentially safer and thus more broadly applicable alternative to non-selective high intensity ultrasound ablation.

bioengineering↗

bioRxiv2019

Multiple Myeloma DREAM Challenge Reveals Epigenetic Regulator PHF19 As Marker of Aggressive Disease

While the past decade has seen meaningful improvements in clinical outcomes for multiple myeloma patients, a subset of patients do not benefit from current therapeutics for unclear reasons. Many gene expression-based models of risk have been developed, but each model uses a different combination of genes and often involve assaying many genes making them difficult to implement. We organized the Multiple Myeloma DREAM Challenge, a crowdsourced effort to develop models of rapid progression in newly diagnosed myeloma patients and to benchmark these against previously published models. This effort lead to more robust predictors and found that incorporating specific demographic and clinical features improved gene expression-based models of high risk. Furthermore, post challenge analysis identified a novel expression-based risk marker and histone modifier, PHF19, which featured prominently in several independent models. Lastly, we show that a simple four feature predictor composed of age, International Staging System stage (ISS), and expression of PHF19 and MMSET performs similarly to more complex models with many more gene expression features included.\n\nKey pointsO_LIMost comprehensive and unbiased assessment of prognostic biomarkers in MM resulting in a robust and parsimonious model.\nC_LIO_LIIdentification of PHF19 as the expression based biomarker most strongly associated with rapid progression in MM patients.\nC_LI

cancer biology↗