Biology subjects

Nowak, J. A.

Publications and source records attributed to Nowak, J. A..

8 recordsLinked to original sources

bioRxiv2026

Pancreatic cancer-associated organ dysfunction promotes muscle autophagy and contributes to peripheral tissue wasting

Normal pancreas function supports both digestion and the hormonal regulation of whole-body metabolism. We find pancreatic ductal adenocarcinoma (PDAC) disrupts the normal function of the remaining pancreas, leading to altered systemic metabolism and peripheral tissue wasting that begins early in disease progression. Using mouse models of PDAC, we find small pancreas tumors lead to both endocrine and exocrine pancreatic dysfunction that results in systemic nutrient depletion and loss of both muscle and fat tissue. Providing free glucose in the diet that is absorbed despite pancreatic exocrine dysfunction causes hyperglycemia and blunts fat wasting without affecting muscle loss. Muscle mass can be restored by free dietary amino acids or pancreatic enzyme supplementation. Exocrine dysfunction causing reduced dietary protein digestion promotes muscle proteolysis and autophagy. Autophagy is a major driver of muscle wasting in PDAC, as muscle-specific deletion of the core autophagy gene Atg7 also reduces muscle wasting. Disrupting muscle autophagy without restoring systemic nutrition slows tumor growth and improves survival of mice with PDAC. Tracing the fate of amino acids released from muscle of mice with PDAC shows redistribution to both tumor and host tissues. Notably, improving nutrition in mice with disrupted muscle autophagy promotes tumor growth. Together, the data argue that early peripheral tissue wasting associated with early pancreatic cancer is driven by altered normal pancreatic organ function that leads to reduced nutrition and enhanced muscle autophagy, releasing nutrients to support both tumor and host metabolism.

cancer biology↗

bioRxiv2025

Strengthening Antisense Oligonucleotide-Mediated Anti-Tumor Immunity via Metal-Organic Framework Nanoparticles

Overexpression of checkpoint proteins, such as programmed death ligand one (PD-L1), prevents immune recognition and enables cancer growth. Current monoclonal antibodies that block PD-L1 tend to be fragile, unable to penetrate tumors, and target cancer at later stages, thus leading to inconsistent patient outcomes. Antisense oligonucleotides (ASOs) provide an alternative to decrease PD-L1 expression, but require frequent high dosing due to fast degradation, rapid clearance, and poor cell uptake. To overcome these issues, we harnessed biocompatible metal-organic framework (MOF) nanoparticles, porous nanomaterials comprising metal nodes and organic linkers, to deliver ASOs. Encapsulating ASOs into MOFs enhances their stability and protection during intracellular delivery, leading to reduced PD-L1 expression and downstream immune recognition. Herein, we synthesized three distinct PD-L1-specific ASOs and loaded them individually into zirconium-based nano-sized NU-1000 MOFs, averaging [~]80% encapsulation efficiency. Release of encapsulated ASOs was sustained up to 7 days ex cellulo. MOF encapsulation increased ASO potency and reduced PD-L1 expression[~] 3-fold and 2-fold in triple negative breast cancer EMT6 and melanoma B16-F10 cells, respectively. We evaluated the impact of MOF-delivered ASOs on PD-L1-expressing immune cells, where we observed ca. 12-fold increases in dendritic cell co-stimulatory marker expression, and amplified T cell activation and proliferation compared to untreated cells (4-fold and 10-fold, respectively). Notably, these changes drove a 3-fold increase in tumor caspase-3 expression, a key mediator for apoptosis. This research highlights how MOFs can be harnessed to bypass ASO limitations without requiring sequence modifications, and offers a broadly applicable platform for improved oligonucleotide delivery for various genes of interest.

bioengineering↗

bioRxiv2025

Pan-cancer spatial characterization of key immune biomarkers in the tumor microenvironment

Deciphering the composition and spatial organization of the tumor immune microenvironment (TiME) is key to uncovering the mechanisms driving cancer progression and treatment response. Spatial biology techniques like multiplex immunofluorescence (mIF) offer detailed insights into the TiME but are often limited to retrospective research studies of individual cancer types. Conversely, bulk omics techniques have been studied in pan-cancer settings but fail to capture single-cell spatial information. Here, we provide a pan-cancer spatial characterization of key biomarkers (CD8, FOXP3, PD-1, PD-L1) of the TiME using data from a mIF assay performed prospectively in a clinical setting on 2,019 tumors across 14 major cancer types. By integrating interpretable compositional and spatial metrics, we identified patterns of TiME variation that are conserved across cancer types and stages. We assess associations between these TiME spatial factors and tumor, genomic, and clinical features, where the results both extend prior findings and uncover new links. Altogether, our findings offer pan-cancer insights of the TiME to further the fields of spatial biology and cancer immunology.

cancer biology↗

bioRxiv2023

Machine learning links T cell function and spatial localization to neoadjuvant immunotherapy and clinical outcome in pancreatic cancer

Tumor molecular datasets are becoming increasingly complex, making it nearly impossible for humans alone to effectively analyze them. Here, we demonstrate the power of using machine learning to analyze a single-cell, spatial, and highly multiplexed proteomic dataset from human pancreatic cancer and reveal underlying biological mechanisms that may contribute to clinical outcome. A novel multiplex immunohistochemistry antibody panel was used to audit T cell functionality and spatial localization in resected tumors from treatment-naive patients with localized pancreatic ductal adenocarcinoma (PDAC) compared to a second cohort of patients treated with neoadjuvant agonistic CD40 (CD40) monoclonal antibody therapy. In total, nearly 2.5 million cells from 306 tissue regions collected from 29 patients across both treatment cohorts were assayed, and more than 1,000 tumor microenvironment (TME) features were quantified. We then trained machine learning models to accurately predict CD40 treatment status and disease-free survival (DFS) following CD40 therapy based upon TME features. Through downstream interpretation of the machine learning models predictions, we found CD40 therapy to reduce canonical aspects of T cell exhaustion within the TME, as compared to treatment-naive TMEs. Using automated clustering approaches, we found improved DFS following CD40 therapy to correlate with the increased presence of CD44+ CD4+ Th1 cells located specifically within cellular spatial neighborhoods characterized by increased T cell proliferation, antigen-experience, and cytotoxicity in immune aggregates. Overall, our results demonstrate the utility of machine learning in molecular cancer immunology applications, highlight the impact of CD40 therapy on T cells within the TME, and identify potential candidate biomarkers of DFS for CD40-treated patients with PDAC.

cancer biology↗

bioRxiv2022

Allosteric regulation of switch-II controls K-Ras oncogenicity

Ras proteins are GTPases that regulate a wide range of cellular processes. The activity of Ras is dependent on its nucleotide-binding status, which is modulated by guanine nucleotide exchange factors (GEFs) and GTPase-activating proteins (GAPs). Previously, we demonstrated that mutation of lysine 104 to glutamine (K104Q) attenuates the transforming capacity of oncogenic K-Ras by interrupting GEF induced nucleotide exchange. To assess the effect of this mutation in vivo, we used CRISPR/Cas9 to generate mouse models carrying the K104Q point mutation in wild-type and conditional K-RasLSL-G12D alleles. Consistent with our previous findings from in vitro studies, the oncogenic activity of K-RasG12D was significantly attenuated by mutation at K104 in vivo. These data demonstrate that lysine at position 104 is critical for the full oncogenic activity of mutant K-Ras and suggest that modification at K104, for example acetylation, may also regulate its activity. In addition, animals homozygous for K104Q were viable, fertile, and arose at Mendelian frequency, indicating that K104Q is not a complete loss of function mutation. Using biochemical and structural analysis, we found that the G12D and K104Q mutations cooperate to suppress GEF-mediated nucleotide exchange, explaining the preferential effect of K104Q on oncogenic K-Ras. Finally, we discovered an allosteric regulatory network consisting of K104 and residues including G75 on switch II (SWII) that is the key for regulating the stability of the helix on SWII. In this allosteric network, K104-G75 interaction might be primary for keeping stabilization of SWII. Given the high frequency of KRAS mutations in human cancers, modulation of this network may provide a unique therapeutic approach.

cancer biology↗

bioRxiv2020

Transcriptional subtype-specific microenvironmental crosstalk and tumor cell plasticity in metastatic pancreatic cancer

Bulk transcriptomic studies have defined classical and basal-like gene expression subtypes in pancreatic ductal adenocarcinoma (PDAC) that correlate with survival and response to chemotherapy; however, the underlying mechanisms that govern these subtypes and their heterogeneity remain elusive. Here, we performed single-cell RNA-sequencing of 23 metastatic PDAC needle biopsies and matched organoid models to understand how tumor cell-intrinsic features and extrinsic factors in the tumor microenvironment (TME) shape PDAC cancer cell phenotypes. We identify a novel cancer cell state that co-expresses basal-like and classical signatures, demonstrates upregulation of developmental and KRAS-driven gene expression programs, and represents a transitional intermediate between the basal-like and classical poles. Further, we observe structure to the metastatic TME supporting a model whereby reciprocal intercellular signaling shapes the local microenvironment and influences cancer cell transcriptional subtypes. In organoid culture, we find that transcriptional phenotypes are plastic and strongly skew toward the classical expression state, irrespective of genotype. Moreover, we show that patient-relevant transcriptional heterogeneity can be rescued by supplementing organoid media with factors found in the TME in a subtype-specific manner. Collectively, our study demonstrates that distinct microenvironmental signals are critical regulators of clinically relevant PDAC transcriptional states and their plasticity, identifies the necessity for considering the TME in cancer modeling efforts, and provides a generalizable approach for delineating the cell-intrinsic versus -extrinsic factors that govern tumor cell phenotypes.

cancer biology↗

bioRxiv2020

Tumor-Immune Partitioning and Clustering (TIPC) algorithm reveals distinct signatures of tumor-immune cell interactions within the tumor microenvironment

Growing evidence supports the importance of understanding tumor-immune spatial relationship in the tumor microenvironment in order to achieve precision cancer therapy. However, existing methods, based on oversimplistic cell-to-cell proximity, are largely confounded by immune cell density and are ineffective in capturing tumor-immune spatial patterns. Here we developed a novel computational algorithm, termed Tumor-Immune Partitioning and Clustering (TIPC), to offer an effective solution for spatially informed tumor subtyping. Our method could measure the extent of immune cell partitioning between tumor epithelial and stromal areas as well as the degree of immune cell clustering. Using a U.S. nation-wide colorectal cancer database, we showed that TIPC could determine tumor subtypes with unique tumor-immune spatial patterns that were significantly associated with patient survival and key tumor molecular features. We also demonstrated that TIPC was robust to parameter settings and readily applicable to different immune cell types. The capability of TIPC in delineating clinically relevant patient subtypes that encapsulate tumor-immune spatial relationship, immune density, and tumor morphology is expected to shed light on underlying immune mechanisms. Hence, TIPC can be a useful bioinformatics tool for effective characterization of the spatial composition of the tumor-immune microenvironment to inform precision immunotherapy.

cancer biology↗

bioRxiv2019

Microenvironmental adaptations drive obesity-associated pancreatic cancer

Obesity is a major modifiable risk factor for pancreatic ductal adenocarcinoma (PDAC), yet how and when obesity contributes to PDAC progression is not well understood. Leveraging an autochthonous mouse model, we demonstrate a causal and reversible role for obesity in early PDAC progression, showing that obesity markedly enhances tumorigenesis, while genetic or dietary induction of weight loss intercepts cancer development. Bulk and single cell molecular analyses of human and murine samples define microenvironmental consequences of obesity that promote tumor development rather than new driver gene mutations. We observe increased inflammation and fibrosis and also provide evidence for significant pancreatic islet cell adaptation in obesity-associated tumors. Specifically, we identify aberrant islet beta cell expression of the peptide hormone cholecystokinin (CCK) in tumors as an adaptive response to obesity. Furthermore, beta cell CCK expression promotes oncogenic Kras-driven pancreatic ductal tumorigenesis. Our studies argue that PDAC progression is driven by local obesity-associated changes in the tumor microenvironment - rather than systemic effects - and implicate endocrine-exocrine signaling beyond insulin in PDAC development. Furthermore, our demonstration that these obesity-associated adaptations are reversible supports the use of anti-obesity strategies to intercept PDAC early during progression.

cancer biology↗