Biology subjects

Welm, A. L.

Publications and source records attributed to Welm, A. L..

14 recordsLinked to original sources

bioRxiv2026

Response to SMAC mimetics in patient-derived models of triple-negative breast cancer relies on RIPK1 activation

Triple-negative breast cancer (TNBC) is a highly metastatic and aggressive breast cancer subtype with limited targeted treatment options. Second mitochondrial activator of caspases (SMAC) mimetics represent a promising therapeutic class for TNBC patients, although they have yet to be approved clinically. Screening a repository of 69 breast cancer patient-derived xenograft organoid (PDxO) lines revealed that approximately 39% were sensitive to the SMAC mimetic birinapant. To define the basis of resistance in lines that did not respond, we compared birinapant-sensitive (S-) and de novo resistant (R-) TNBC PDxOs. Birinapant caused degradation of inhibitor of apoptosis proteins (IAPs) in both groups but failed to induce cell death in R-PDxOs. We determined that R-PDxOs were susceptible to certain types of apoptosis but were specifically resistant to TNFR-mediated cell death, an integral pathway involved in SMAC mimetic response. Moreover, RIPK1 activation via autophosphorylation, a critical event in TNFR-mediated apoptosis, was absent in both R-PDxOs and PDxOs selected for acquired birinapant resistance. Pharmacologic inhibition or degradation of RIPK1 protected S-PDxOs from birinapant-induced cell death, demonstrating that RIPK1 activation is required for response in TNBC. To investigate how to restore RIPK1 activation in R-PDxOs, we discovered that HOIP, an E3 ubiquitin ligase that inhibits RIPK1 autophosphorylation, was more abundant in R-PDxOs compared to S-PDxOs. Inhibiting HOIP activity restored RIPK1 autophosphorylation and sensitized a subset of R-PDxOs to birinapant. Together, these findings identify impaired RIPK1 autophosphorylation as a mechanism of birinapant resistance in TNBC and suggest that RIPK1 activation state may distinguish SMAC mimetic-sensitive and -resistant tumors. Targeting HOIP may provide a strategy to overcome resistance in selected tumors.

cancer biology↗

bioRxiv2026

Loss of short-form Ron promotes B and T cell cooperation to prevent outgrowth of breast cancer bone metastasis

While immunotherapy has great potential to eradicate tumors, success in metastatic breast cancer is limited. Bone metastasis, the most common site for breast cancer metastasis, has been associated with weakened anti-tumor immunity, both in the bone and in other metastatic sites. Additional strategies promoting anti-tumor immunity are needed. Using the MMTV-PyMT intratibial model of breast cancer bone metastasis, we discovered that deletion of host short-form Ron (Ron SF-/-) protected against bone metastatic outgrowth by promoting strong infiltration of lymphocytes, including B cells, into tumors at the micrometastasis stage. Transcriptionally, Ron SF-/- B cells were more active and inflammatory compared to wildtype. Elimination of mature B cells (JH-/-) rescued tumor growth in Ron SF-/- mice, indicating that mature B cells were necessary for anti-tumor immunity and protection against bone metastasis. In Ron SF-/- hosts, T follicular helper (Tfh) cells were abundant in tumor-enriched regions of bone, suggesting interactions between B and T cells. B-T cell cooperation was further supported by attenuation of CD4 and CD8 T cell tumor infiltration in Ron SF-/-JH-/- hosts and, conversely, diminished B cell tumor infiltration and rescue of tumor growth in Ron SF-/- hosts lacking CD4 or CD8 T cells. B cells were not required to protect Ron SF-/- mice from lung metastasis, indicating a tissue-dependent anti-tumor role for B cells. These data support a positive feedback loop between B and T cells regulated by SF-Ron and reveal the anti-tumor potential of B cells in the bone.

cancer biology↗

bioRxiv2026

The coumarin derivative X6632 is a pan-ID protein inhibitor that suppresses tumor growth by targeting cancer cells and the tumor-associated microvasculature

Inhibitor of DNA binding (ID) proteins are key regulators of tumor cell stemness, therapy resistance and pathological angiogenesis in multiple cancer types and other diseases. Here, we characterize the coumarin-derived compound X6632 as a pan-ID inhibitor with dual activity against tumor cells and the tumor-associated microvasculature in a number of human and murine models. X6632 efficiently suppressed ID protein expression, inhibited the proliferation, migration, invasion of melanoma cells, and impaired multiple endothelial cell functions, including proliferation, migration, invasion, tube formation and sprouting in vitro. In back-to-back comparisons, X6632 exhibited an approximately ten-fold higher efficacy compared to the first-generation ID antagonist AGX51. In vivo, X6632 potently reduced pathological (neo)vascularization in established angiogenesis models, including oxygen-induced retinopathy and in Matrigel plug assays. It also significantly decreased blood vessel density in syngeneic melanoma models, delayed tumor growth and, when combined with immune checkpoint blockade, achieved superior tumor control compared with either monotherapy. Moreover, X6632 inhibited clonogenic growth in several breast cancer models, and robustly suppressed the growth of triple negative breast cancer in vivo, both in the highly aggressive 4T1 syngeneic model and in patient-derived xenografts. Collectively, these data establish X6632 as a second-generation, pan-ID protein inhibitor that can simultaneously target malignant cells and the tumor-supporting vasculature, and support the further pre-clinical development of the compound for the treatment of melanoma, breast cancer and potentially additional ID-dependent malignancies, as well as diseases driven by pathological neoangiogenesis.

cancer biology↗

bioRxiv2025

Determination of Drug Sensitivity in Patient Derived Models of Breast Cancer by Multiparametric QPI

Functional precision oncology seeks to match patients with effective therapies by empirically testing patient-derived samples for drug sensitivity in the laboratory. However, existing approaches require significant sample expansion time and expense prior to analysis, rendering them impractical for routine clinical testing. Quantitative phase imaging (QPI) provides a potential path forward by directly measuring responses at single cell resolution without the need for extensive sample expansion. In previous work, we demonstrated that multiple, independent parameters of cellular response to therapeutic agents can be derived from QPI data, an approach we call multiparametric QPI (mQPI). Here, we demonstrate application of mQPI using cells from patient derived xenograft organoid (PDxO) models, as well as cells viably frozen direct from patients. Using mQPI with breast cancer PDxO models, we uncover distinct drug responses for cells originating from different anatomic sites in the same patient and resolve cellular heterogeneity of response in a model of acquired therapeutic resistance. We also show that mQPI can detect drug responses in viably frozen primary patient samples, either direct from thaw or after a short term expansion of only 2 weeks. Overall, these data provide proof-of-principle for application of mQPI to a range of sample types, including cryopreserved material direct from patients. This underscores the clinical potential of mQPI as a time- and materials-efficient alternative to current methods in functional precision oncology.

bioengineering↗

bioRxiv2024

A precision oncology-focused deep learning framework for personalized selection of cancer therapy

Precision oncology matches tumors to targeted therapies based on the presence of actionable molecular alterations. However, most tumors lack actionable alterations, restricting treatment options to cytotoxic chemotherapies for which few data-driven prioritization strategies currently exist. Here, we report an integrated computational/experimental treatment selection approach applicable for both chemotherapies and targeted agents irrespective of actionable alterations. We generated functional drug response data on a large collection of patient-derived tumor models and used it to train ScreenDL, a novel deep learning-based cancer drug response prediction model. ScreenDL leverages the combination of tumor omic and functional drug screening data to predict the most efficacious treatments. We show that ScreenDL accurately predicts response to drugs with diverse mechanisms, outperforming existing methods and approved biomarkers. In our preclinical study, this approach achieved superior clinical benefit and objective response rates in breast cancer patient-derived xenografts, suggesting that testing ScreenDL in clinical trials may be warranted.

cancer biology↗

bioRxiv2024

Patient-Derived Xenografts of Triple-Negative Breast Cancer Enable Deconvolution and Prediction of Chemotherapy Responses

Chemotherapy regimens for triple-negative breast cancer (TNBC) combine agents without knowing which agents drive response. Consequently, predictors derived from multi-agent regimens cannot be assumed to generalize to individual drugs or other regimens, motivating development of treatment-matched predictors. Here, we used TNBC patient-derived xenografts (PDXs) treated with carboplatin, docetaxel, or the combination to deconvolute drug-specific responses and identify associated molecular features. Combination treatment rarely improved upon the best single agent, with enhanced responses in only 13% of PDXs and antagonism in a comparable fraction. Proteogenomic analyses identified high cytokeratin-5 (KRT5) as a general marker of chemotherapy responsiveness and KRT5 immunohistochemistry discriminated responsive PDXs (AUROC, 0.83). To train treatment-specific predictors, we integrated these data with independent PDX and clinical cohorts with responses assessed after anthracycline-free platinum, taxane, or platinum-taxane therapy, ensuring response corresponded to the modeled treatment. Four feature selection strategies yielded largely nonoverlapping biomarker panels converging on treatment-relevant pathways. On independent test data, RNA-based predictors of complete response (CR) to platinum-based (carboplatin or cisplatin) and taxane-based (docetaxel or paclitaxel) chemotherapy achieved AUROCs of 0.80 and 0.86, respectively. For platinum-taxane regimens (carboplatin plus docetaxel or paclitaxel), proteomic-guided feature selection generated a 10-biomarker, protein- informed RNA predictor of pathologic complete response (pCR) that outperformed RNA-only feature selection and achieved an AUROC of 0.85 in an independent clinical cohort, while retaining practicality as an RNA-based assay. Treatment-matched integration of multi-omic PDX and clinical datasets provides a framework for chemotherapy-specific predictors with clinically relevant performance, supporting biomarker-guided precision selection and treatment optimization for patients with TNBC. Statement of significanceIntegration of multi-omic data from patient-derived xenografts with treatment-matched clinical cohorts yielded three retrospectively validated predictors of platinum, taxane, and platinum+taxane response, enabling biomarker-guided chemotherapy selection for patients with triple-negative breast cancer.

cancer biology↗

bioRxiv2022

A pan-cancer PDX histology image repository with genomic and pathological annotations for deep learning analysis

Patient-derived xenografts (PDXs) model human intra-tumoral heterogeneity in the context of the intact tissue of immunocompromised mice. Histological imaging via hematoxylin and eosin (H&E) staining is performed on PDX samples for routine assessment and, in principle, captures the complex interplay between tumor and stromal cells. Deep learning (DL)-based analysis of large human H&E image repositories has extracted inter-cellular and morphological signals correlated with disease phenotype and therapeutic response. Here, we present an extensive, pan-cancer repository of nearly 1,000 PDX and paired human progenitor H&E images. These images, curated from the PDXNet consortium, are associated with genomic and transcriptomic data, clinical metadata, pathological assessment of cell composition, and, in several cases, detailed pathological annotation of tumor, stroma, and necrotic regions. We demonstrate that DL can be applied to these images to classify tumor regions and to predict xenograft-transplant lymphoproliferative disorder, the unintended outgrowth of human lymphocytes at the transplantation site. This repository enables PDX-specific, investigations of cancer biology through histopathological analysis and contributes important model system data that expand on existing human histology repositories. We expect the PDXNet Image Repository to be valuable for controlled digital pathology analysis, both for the evaluation of technical issues such as stain normalization and for development of novel computational methods based on spatial behaviors within cancer tissues.

bioinformatics↗

bioRxiv2022

Estrogen receptor alpha mutations regulate gene expression and cell growth in breast cancer through microRNAs

Estrogen receptor (ER) mutations occur in up to 30% of metastatic ER-positive breast cancers. Recent data has shown that ER mutations impact the expression of thousands of genes not typically regulated by wildtype ER. While the majority of these altered genes can be explained by constant activity of mutant ER or genomic changes such as altered ER binding and chromatin accessibility, as much as 33% remain unexplained, indicating the potential for post-transcriptional effects. Here we explored the role of microRNAs in mutant ER-driven gene regulation and identified several microRNAs that are dysregulated in ER mutant cells. These differentially regulated microRNAs target a significant portion of mutant-specific genes involved in key cellular processes. When the activity of microRNAs is altered using mimics or inhibitors, significant changes are observed in gene expression and cellular proliferation related to mutant ER. An in-depth evaluation of miR-301b led us to discover an important role for PRKD3 in the proliferation of ER mutant cells. Our findings show that microRNAs contribute to mutant ER gene regulation and cellular effects in breast cancer cells.

cancer biology↗

bioRxiv2021

Low-affinity CAR T cells exhibit reduced trogocytosis, preventing fratricide and antigen-negative tumor escape while preserving anti-tumor activity

Chimeric antigen receptor (CAR) T cells using the high-affinity CD19 binding domain FMC63 are an effective treatment for patients with relapsed and aggressive B cell lymphoma. However, antigen loss and poor CAR T cell persistence remain common causes for relapse in these patients. Using primary patient samples, we now show that FMC63-based CAR T cells confer rapid antigen loss in all major tumor types currently approved for treatment with CD19 CAR T cells via trogocytosis, the stripping of antigen from tumor cells by CAR T cells. We show that CAR T cell-mediated trogocytosis can be dramatically reduced across a wide range of B cell malignancies by replacing FMC63 with a low affinity CD19 antibody. This reduction in trogocytosis does not alter the direct anti-tumor activity of CD19 CAR T cells but prevents the emergence of antigen-negative tumor cells and significantly increases CAR T cell viability by reducing fratricide of CD19 CAR T cells following trogocytosis. TEASERA reduction in CAR affinity does not affect tumor killing but prolongs T cell persistence and prevents antigen-negative tumor escape.

bioengineering↗

bioRxiv2021

PDXNet Portal: Patient-Derived Xenograft model, data, workflow, and tool discovery

We created the PDX Network (PDXNet) Portal (https://portal.pdxnetwork.org/) to centralize access to the National Cancer Institute-funded PDXNet consortium resources (i.e., PDX models, sequencing data, treatment response data, and bioinformatics workflows), to facilitate collaboration among researchers, and to make resources easily available for research. The portal includes sections for resources, analysis results, metrics for PDXNet activities, data processing protocols, and training materials for processing PDX data. The initial portal release highlights PDXNet model and data resources, including 334 new models across 33 cancer types. Tissue samples of these models were deposited in the NCIs Patient-Derived Model Repository (PDMR) for public access. These models have 2,822 associated sequencing files from 873 samples across 307 patients, which are hosted on the Cancer Genomics Cloud powered by Seven Bridges and the NCI Cancer Data Service for long-term storage and access with dbGaP permissions. The portal also includes results from standardized analysis workflows on PDXNet sequencing files and PDMR data (2,594 samples from 463 patients across 78 disease types). These 15 analysis workflows for whole-exome and RNA-Seq data are freely available, robust, validated, and standardized. The model and data lists will grow substantially over the next two years and will be continuously updated as new data are available. PDXNet models support multi-agent treatment studies, determination of sensitivity and resistance mechanisms, and preclinical trials. The PDXNet portal is a centralized location for these data and resources, which we expect to be of significant utility for the cancer research community.

cancer biology↗

bioRxiv2021

Laterally transferred macrophage mitochondria acts as a signaling source promoting cancer cell proliferation

Lateral transfer of mitochondria occurs in many physiological and pathological conditions. Given that mitochondria provide essential energy for cellular activities, mitochondrial transfer is currently thought to promote the rescue of damaged cells. We report that mitochondrial transfer occurs between macrophages and breast cancer cells, leading to increased cancer cell proliferation. Unexpectedly, transferred macrophage mitochondria are dysfunctional, lacking mitochondrial membrane potential. Rather than performing essential mitochondrial activities, transferred mitochondria accumulate reactive oxygen species which activates ERK signaling, indicating that transferred mitochondria act as a signaling source that promotes cancer cell proliferation. We also demonstrate that pro-tumorigenic M2-like macrophages exhibit increased mitochondrial transfer to cancer cells. Collectively, our findings reveal how mitochondrial transfer is regulated and leads to sustained functional changes in recipient cells. One-Sentence SummaryLateral transfer of macrophage mitochondria acts as a ROS signaling source, regulating cancer cell proliferation through ERK signaling.

cancer biology↗

bioRxiv2021

A breast cancer patient-derived xenograft and organoid platform for drug discovery and precision oncology

Model systems that recapitulate the complexity of human tumors and the reality of variable treatment responses are urgently needed to better understand cancer biology and to develop more effective cancer therapies. Here we report development and characterization of a large bank of patient-derived xenografts (PDX) and matched organoid cultures from tumors that represent some of the greatest unmet needs in breast cancer research and treatment. These include endocrine-resistant, treatment-refractory, and metastatic breast cancers and, in some cases, multiple tumor collections from the same patients. The models can be grown long-term with high fidelity to the original tumors. We show that development of matched PDX and PDX-derived organoid (PDxO) models facilitates high-throughput drug screening that is feasible and cost-effective, while also allowing in vivo validation of results. Our data reveal consistency between drug screening results in organoids and drug responses in breast cancer PDX. Moreover, we demonstrate the feasibility of using these patient-derived models for precision oncology in real time with patient care, using a case of a triple negative breast cancer with early metastatic recurrence as an example. Our results uncovered an FDA-approved drug with high efficacy against the models. Treatment with the PDxO-directed therapy resulted in a complete response for the patient and a progression-free survival period more than three times longer than her previous therapies. This work provides valuable new methods and resources for functional precision medicine and drug development for human breast cancer. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=189 HEIGHT=200 SRC="FIGDIR/small/433268v2_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@134d5cdorg.highwire.dtl.DTLVardef@1c0a419org.highwire.dtl.DTLVardef@556a4forg.highwire.dtl.DTLVardef@1b68c9c_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2020

ScRNA-seq reveals tumor microenvironment remodeling induced by local intervention-based immunotherapy

Laser immunotherapy (LIT) combines local photothermal therapy (PTT), to disrupt tumor homeostasis and release tumor antigens, and an intratumorally administered immunostimulant, N-dihydrogalactochitosan (GC), to induce antitumor immune responses. We performed single-cell RNA sequencing on tumor-infiltrating leukocytes of MMTV-PyMT mouse mammary tumors to characterize LIT-induced myeloid and lymphoid compartment remodeling. Analysis of 49,380 single cell transcriptomes from different treatment groups revealed that proinflammatory IFN, IFN{gamma}, and TNF cytokine signaling pathways were enriched in both lymphoid and myeloid cells isolated from LIT-treated tumors. The CD4+ and CD8+ T cells in LIT treated tumors resided in an activated state while immune cells in untreated and PTT-treated tumors remained in a neutral/resting state. Additionally, monocytes recruited into the LIT-treated tumors were driven towards proinflammatory M1-like macrophage phenotypes or monocyte-derived dendritic cells. Our results reveal that LIT prompts immunological remodeling of the tumor microenvironment by initiating broad proinflammatory responses to drive antitumor immunity. STATEMENT OF SIGNIFICANCETranscriptome profiling of tumor infiltrating leukocytes revealed that localized laser immunotherapy (LIT) greatly enhanced antitumor T cell activity by promoting proinflammatory myeloid cell responses within the tumor microenvironment. This manuscript demonstrates that LIT broadly stimulates antitumor immunity and has great potential to synergize with current immunotherapies to increase their efficacy.

cell biology↗

bioRxiv2019

Conservation of copy number profiles during engraftment and passaging of patient-derived cancer xenografts

Patient-derived xenografts (PDXs) are resected human tumors engrafted into mice for preclinical studies and therapeutic testing. It has been proposed that the mouse host affects tumor evolution during PDX engraftment and propagation, impacting the accuracy of PDX modeling of human cancer. Here we exhaustively analyze copy number alterations (CNAs) in 1451 PDX and matched patient tumor (PT) samples from 509 PDX models. CNA inferences based on DNA sequencing and microarray data displayed substantially higher resolution and dynamic range than gene expression-based inferences, and they also showed strong CNA conservation from PTs through late-passage PDXs. CNA recurrence analysis of 130 colorectal and breast PT/PDX-early/PDX-late trios confirmed high-resolution CNA retention. We observed no significant enrichment of cancer-related genes in PDX-specific CNAs across models. Moreover, CNA differences between patient and PDX tumors were comparable to variations in multi-region samples within patients. Our study demonstrates the lack of systematic copy number evolution driven by the PDX mouse host.

cancer biology↗