Foltz, S. | bioRxiv Science

bioRxiv2025

Longitudinal multi-omic profiling uncovers immune escape and predictors of response in multiple myeloma

Multiple myeloma (MM) is an incurable malignancy of clonally expanded plasma cells shaped by complex interactions with the immune microenvironment. To investigate immune factors driving treatment response and resistance, we conducted multi-omics profiling including CD138neg single-cell RNA sequencing of 243 bone marrow samples from 102 patients (631,226 cells) and CD138pos bulk RNA and whole-genome sequencing from 209 samples. Longitudinal analyses revealed that interferon gamma signaling impairs T cell memory after autologous stem cell transplant, while naive B cell abundance and immunoglobulin diversity correlated with improved progression-free survival (HR = 0.48, p = 2.3e-4). At disease progression, MM cells upregulated cancer-testis antigens and immune effector genes, with concurrent B cell depletion, enrichment of myeloid-derived suppressor cell genes in monocytes, and T cell exhaustion. These findings highlight dynamic immune-tumor interactions, identifying naive B cell reconstitution as a biomarker of durable response, and cancer-testis antigens as potential targets for high-risk disease at progression. Statement of SignificanceLongitudinal profiling of multiple myeloma and the immune microenvironment revealed dynamic immune-tumor interactions across the disease course. Dysfunctional CD8 T cells limited memory formation post-transplant, while naive B recovery associated with sustained treatment response. At progression, cancer-testis antigen expression associated with immunosuppression, revealing novel mechanisms of immune escape.

cancer biology↗

bioRxiv2019

Myosoft: an automated muscle histology analysis tool using machine learning algorithm utilizing FIJI/ImageJ software.

BackgroundSkeletal muscle is comprised of a heterogeneous population of muscle fibers which can be classified by their metabolic and contractile properties (fiber \"types\"). Fiber type is a primary determinant of muscle function along with fiber size (cross-sectional area). The fiber type composition of a muscle responds to physiological changes like exercise and aging and is often altered in disease states. Thus, analysis of fiber size and type in histological muscle preparations is a useful method for quantifying key indicators of muscle function and for measuring responses to a variety of stimuli or stressors. These analyses are near-ubiquitous in the fields of muscle physiology and myopathy, but are most commonly performed manually, which is highly labor- and time-intensive. To offset this obstacle, we developed Myosoft, a novel method to automate morphometric and fiber type analysis in muscle sections stained with fluorescent antibodies.\n\nMethodsMuscle sections were stained for cell membrane (laminin) and myofiber type (myosin heavy chain isoforms). Myosoft, running in the open access software platform FIJI (ImageJ), was used to analyze myofiber size and type in transverse sections of entire gastrocnemius/soleus muscles.\n\nResultsMyosoft provides accurate analysis of muscle histology >50-times faster than manual analysis. We demonstrate that Myosoft is capable of handling high-content images even when image or staining quality is suboptimal, which is a marked improvement over currently available, comparable programs.\n\nConclusionsMyosoft is a reliable, accurate, high-throughput, and convenient tool to analyze high-content muscle histology. Myosoft is freely available to download from Github at https://github.com/Hyojung-Choo/Myosoft/tree/Myosoft-hub.

physiology↗