Altered bile acid and coproporphyrin-I disposition in patients with autosomal dominant polycystic kidney disease.

AIMS: Serum, liver and urinary bile acids are increased, and hepatic transport protein levels are decreased in a non-clinical model of polycystic kidney disease. Similar changes in patients with autosomal dominant polycystic kidney disease (ADPKD) may predispose them to drug-induced liver injury (DILI) and hepatic drug-drug interactions (DDIs). Systemic coproporphyrin-I (CP-I), an endogenous biomarker for hepatic OATP1B function and MRP2 substrate, is used to evaluate OATP1B-mediated DDI risk in humans. In this clinical observational cohort-comparison study, bile acid profiles and CP-I concentrations in healthy volunteers and patients with ADPKD were compared. METHODS: Serum and urine samples from healthy volunteers (n = 16) and patients with ADPKD (n = 8) were collected. Serum bile acids, and serum and urine CP-I concentrations, were quantified by ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS). RESULTS: Patients with ADPKD exhibited increased serum concentrations of total (1.3-fold) and taurine-conjugated (2.8-fold) bile acids compared to healthy volunteers. Specifically, serum concentrations of six bile acids known to be more hydrophobic/hepatotoxic (glycochenodeoxycholate, taurochenodeoxycholate, taurodeoxycholate, lithocholate, glycolithocholate and taurolithocholate) were increased (1.5-, 2.9-, 2.8-, 1.6-, 1.7- and 2.7-fold, respectively) in patients with ADPKD. Furthermore, serum CP-I concentrations were elevated and the renal clearance of CP-I was reduced in patients with ADPKD compared to healthy volunteers. CONCLUSIONS: Increased exposure to bile acids may increase susceptibility to DILI in some patients with ADPKD. Furthermore, the observed increase in serum CP-I concentrations could be attributed, in part, to impaired OATP1B function in patients with ADPKD, which could increase the risk of DDIs involving OATP1B substrates compared to healthy volunteers.

Leveraging real-world data to predict cancer cachexia stage, quality of life, and survival in a racially and ethnically diverse multi-institutional cohort of treatment-naïve patients with pancreatic ductal adenocarcinoma.

Introduction: Cancer-associated cachexia (CC) is a progressive syndrome characterized by unintentional weight loss, muscle atrophy, fatigue, and poor outcomes that affects most patients with pancreatic ductal adenocarcinoma (PDAC). The ability to identify and classify CC stage along its continuum early in the disease process is challenging but critical for management. Objectives: The main objective of this study was to determine the prevalence of CC stage overall and by sex and race and ethnicity among treatment-naïve PDAC cases using clinical, nutritional, and functional criteria. Secondary objectives included identifying the prevalence and predictors of higher symptom burden, supportive care needs, and quality of life (QoL), and examining their influence on overall survival (OS). Materials and methods: A population-based multi-institutional prospective cohort study of patients with PDAC was conducted between 2018 and 2021 by the Florida Pancreas Collaborative. Leveraging patient-reported data and laboratory values, participants were classified at baseline into four stages [non-cachexia (NCa), pre-cachexia (PCa), cachexia (Ca), and refractory cachexia (RCa)]. Multivariate regression, Kaplan Meier analyses, and Cox regression were conducted to evaluate associations. Results: CC stage was estimated for 309 PDAC cases (156 females, 153 males). The overall prevalence of NCa, PCa, Ca, and RCa was 12.9%, 24.6%, 54.1%, and 8.4%, respectively. CC prevalence across all CC stages was highest for males and racial and ethnic minorities. Criteria differentiated NCa cases from other groups, but did not distinguish PCa from Ca. The most frequently reported symptoms included weight loss, fatigue, pain, anxiety, and depression, with pain significantly worsening over time. The greatest supportive care needs included emotional and physical domains. Males, Black people, and those with RCa had the worst OS. Conclusions: Using clinical, nutritional, and functional criteria, nearly one-quarter of the PDAC cases in our diverse, multi-institutional cohort had PCa and 62.5% had Ca or RCa at the time of diagnosis. The PCa estimate is higher than that reported in prior studies. We recommend these criteria be used to aid in CC classification, monitoring, and management of all incident PDAC cases. Findings also highlight the recommendation for continued emotional support, assistance in alleviating pain, and supportive care needs throughout the PDAC treatment journey.

Multimodal data integration for oncology in the era of deep neural networks: a review.

Cancer research encompasses data across various scales, modalities, and resolutions, from screening and diagnostic imaging to digitized histopathology slides to various types of molecular data and clinical records. The integration of these diverse data types for personalized cancer care and predictive modeling holds the promise of enhancing the accuracy and reliability of cancer screening, diagnosis, and treatment. Traditional analytical methods, which often focus on isolated or unimodal information, fall short of capturing the complex and heterogeneous nature of cancer data. The advent of deep neural networks has spurred the development of sophisticated multimodal data fusion techniques capable of extracting and synthesizing information from disparate sources. Among these, Graph Neural Networks (GNNs) and Transformers have emerged as powerful tools for multimodal learning, demonstrating significant success. This review presents the foundational principles of multimodal learning including oncology data modalities, taxonomy of multimodal learning, and fusion strategies. We delve into the recent advancements in GNNs and Transformers for the fusion of multimodal data in oncology, spotlighting key studies and their pivotal findings. We discuss the unique challenges of multimodal learning, such as data heterogeneity and integration complexities, alongside the opportunities it presents for a more nuanced and comprehensive understanding of cancer. Finally, we present some of the latest comprehensive multimodal pan-cancer data sources. By surveying the landscape of multimodal data integration in oncology, our goal is to underline the transformative potential of multimodal GNNs and Transformers. Through technological advancements and the methodological innovations presented in this review, we aim to chart a course for future research in this promising field. This review may be the first that highlights the current state of multimodal modeling applications in cancer using GNNs and transformers, presents comprehensive multimodal oncology data sources, and sets the stage for multimodal evolution, encouraging further exploration and development in personalized cancer care.

Defining and Addressing Research Priorities in Cancer Cachexia through Transdisciplinary Collaboration.

For many patients, the cancer continuum includes a syndrome known as cancer-associated cachexia (CAC), which encompasses the unintended loss of body weight and muscle mass, and is often associated with fat loss, decreased appetite, lower tolerance and poorer response to treatment, poor quality of life, and reduced survival. Unfortunately, there are no effective therapeutic interventions to completely reverse cancer cachexia and no FDA-approved pharmacologic agents; hence, new approaches are urgently needed. In May of 2022, researchers and clinicians from Moffitt Cancer Center held an inaugural retreat on CAC that aimed to review the state of the science, identify knowledge gaps and research priorities, and foster transdisciplinary collaborative research projects. This review summarizes research priorities that emerged from the retreat, examples of ongoing collaborations, and opportunities to move science forward. The highest priorities identified include the need to (1) evaluate patient-reported outcome (PRO) measures obtained in clinical practice and assess their use in improving CAC-related outcomes; (2) identify biomarkers (imaging, molecular, and/or behavioral) and novel analytic approaches to accurately predict the early onset of CAC and its progression; and (3) develop and test interventions (pharmacologic, nutritional, exercise-based, and through mathematical modeling) to prevent CAC progression and improve associated symptoms and outcomes.

Impact of deprivation and preferential usage on functional connectivity between early visual cortex and category selective visual regions.

Human behavior can be remarkably shaped by experience, such as the removal of sensory input. Many studies of conditions such as stroke, limb amputation, and vision loss have examined how the removal of input changes brain function. However, an important question has yet to be answered: when input is lost, does the brain change its connectivity to preferentially use some remaining inputs over others? In individuals with healthy vision, the central portion of the retina is preferentially used for everyday visual tasks, due to its ability to discriminate fine details. However, when central vision is lost in conditions like macular degeneration, peripheral vision must be relied upon for those everyday tasks, with certain portions receiving "preferential" usage over others. Using resting-state fMRI collected during total darkness, we examined how deprivation and preferential usage influence the intrinsic functional connectivity of sensory cortex by studying individuals with selective vision loss due to late stages of macular degeneration. We found that cortical regions representing spared portions of the peripheral retina, regardless of whether they are preferentially used, exhibit plasticity of intrinsic functional connectivity in macular degeneration. Cortical representations of spared peripheral retinal locations showed stronger connectivity to MT, a region involved in processing motion. These results suggest that long-term loss of central vision can produce widespread effects throughout spared representations in early visual cortex, regardless of whether those representations are preferentially used. These findings support the idea that connections to visual cortex maintain the capacity for change well after critical periods of visual development. Highlights: Portions of early visual cortex representing central vs. peripheral vision exhibit different patterns of connectivity to category-selective visual regions.When central vision is lost, cortical representations of peripheral vision display stronger functional connections to MT than central representations.When central vision is lost, connectivity to regions selective for tasks that involve central vision (FFA and PHA) are not significantly altered.These effects do not depend on which locations of peripheral vision are used more.

Structure-independent machine-learning predictions of the CDK12 interactome.

Cyclin-dependent kinase 12 (CDK12) is a critical regulatory protein involved in transcription and DNA repair processes. Dysregulation of CDK12 has been implicated in various diseases, including cancer. Understanding the CDK12 interactome is pivotal for elucidating its functional roles and potential therapeutic targets. Traditional methods for interactome prediction often rely on protein structure information, limiting applicability to CDK12 characterized by partly disordered terminal C region. In this study, we present a structure-independent machine-learning model that utilizes proteins' sequence and functional data to predict the CDK12 interactome. This approach is motivated by the disordered character of the CDK12 C-terminal region mitigating a structure-driven search for binding partners. Our approach incorporates multiple data sources, including protein-protein interaction networks, functional annotations, and sequence-based features, to construct a comprehensive CDK12 interactome prediction model. The ability to predict CDK12 interactions without relying on structural information is a significant advancement, as many potential interaction partners may lack crystallographic data. In conclusion, our structure-independent machine-learning model presents a powerful tool for predicting the CDK12 interactome and holds promise in advancing our understanding of CDK12 biology, identifying potential therapeutic targets, and facilitating precision-medicine approaches for CDK12-associated diseases.

Implementation of a High-Accuracy Targeted Gene Expression Panel for Clinical Care.

This study describes the validation of a clinical RNA expression panel with evaluation of concordance between gene copy gain by a next-generation sequencing (NGS) assay and high gene expression by an RNA expression panel. The RNA Salah Targeted Expression Panel (RNA STEP) was designed with input from oncologists to include 204 genes with utility for clinical trial prescreening and therapy selection. RNA STEP was validated with the nanoString platform using remnant formalin-fixed, paraffin-embedded-derived RNA from 102 patients previously tested with a validated clinical NGS panel. The repeatability, reproducibility, and concordance of RNA STEP results with NGS results were evaluated. RNA STEP demonstrated high repeatability and reproducibility, with excellent correlation (r > 0.97, P < 0.0001) for all comparisons. Comparison of RNA STEP high gene expression (log2 ratio ≥ 2) versus NGS DNA-based gene copy number gain (copies ≥ 5) for 38 mutually covered genes revealed an accuracy of 93.0% with a positive percentage agreement of 69.4% and negative percentage agreement of 93.8%. Moderate correlation was observed between platforms (r = 0.53, P < 0.0001). Concordance between high gene expression and gene copy number gain varied by specific gene, and some genes had higher accuracy between assays. Clinical implementation of RNA STEP provides gene expression data complementary to NGS and offers a tool for prescreening patients for clinical trials.

Pathogenic Roles for RNASET2 in Clear Cell Renal Cell Carcinoma.

A specific splicing isoform of RNASET2 is associated with worse oncologic outcomes in clear cell renal cell carcinoma (ccRCC). However, the interplay between wild-type RNASET2 and its splice variant and how this might contribute to the pathogenesis of ccRCC remains poorly understood. We sought to better understand the relationship of RNASET2 in the pathogenesis of ccRCC and the interplay with a pathogenic splicing isoform (RNASET2-SV) and the tumor immune microenvironment. Using data from The Cancer Genome Atlas and Clinical Proteomic Tumor Analysis Consortium, we correlated clinical variables to RNASET2 expression and the presence of a specific RNASET2-SV. Immunohistochemical staining with matched RNA sequencing of ccRCC patients was then utilized to understand the spatial relationships of RNASET2 with immune cells. Finally, in vitro studies were performed to demonstrate the oncogenic role of RNASET2 and highlight its potential mechanisms. RNASET2 gene expression is associated with higher grade tumors and worse overall survival in The Cancer Genome Atlas cohort. The presence of the RNASET2-SV was associated with increased expression of the wild-type RNASET2 protein and epigenetic modifications of the gene. Immunohistochemical staining revealed increased intracellular accumulation of RNASET2 in patients with increased RNA expression of RNASET2-SV. In vitro experiments reveal that this accumulation results in increased cell proliferation, potentially from altered metabolic pathways. RNASET2 exhibits a tumor-promoting role in the pathogenesis of ccRCC that is increased in the presence of a specific RNASET2-SV and associated with changes in the cellular localization of the protein.

Clinical Presentation and Genomic Analysis of HPV-Related Squamous Cell Carcinoma of the Larynx in Two Young Female Patients.

Laryngeal cancer most frequently develops in males aged 60-70 years with a history of tobacco and/or alcohol use, while fewer cases occur in young patients in which tobacco and alcohol are often absent or less significant, highlighting the importance of other etiologies. We present cases of human papillomavirus (HPV)-associated laryngeal cancer in two previously healthy young women. A retrospective case review was carried out for both patients. DNA was extracted from the primary tumors and matched to normal tissue or blood, HPV genotype was determined by PCR and whole exome sequencing was carried out. Genomic results were pooled with laryngeal cancer patients from the cancer genome atlas (TCGA) dataset. The first patient was an 18-year-old female who underwent laryngectomy followed by adjuvant radiation. The second was a 24-year-old female who received chemoradiation. The first patient has remained disease-free for 16 years and the second for two years; both continue to be monitored. One tumor was positive for HPV45 and had mutations in FAT1 and FAT2; the other was positive for HPV31 and had mutations at NOTCH1, MAPK1, and HIST1H2AK. Both tumors had wild-type TP53 alleles. We bring attention to HPV as an etiology of laryngeal carcinoma in young patients, which may have implications for the treatment and prognosis of similar patients.

RBFOX2 deregulation promotes pancreatic cancer progression and metastasis through alternative splicing.

RNA splicing is an important biological process associated with cancer initiation and progression. However, the contribution of alternative splicing to pancreatic cancer (PDAC) development is not well understood. Here, we identify an enrichment of RNA binding proteins (RBPs) involved in splicing regulation linked to PDAC progression from a forward genetic screen using Sleeping Beauty insertional mutagenesis in a mouse model of pancreatic cancer. We demonstrate downregulation of RBFOX2, an RBP of the FOX family, promotes pancreatic cancer progression and liver metastasis. Specifically, we show RBFOX2 regulates exon splicing events in transcripts encoding proteins involved in cytoskeletal remodeling programs. These exons are differentially spliced in PDAC patients, with enhanced exon skipping in the classical subtype for several RBFOX2 targets. RBFOX2 mediated splicing of ABI1, encoding the Abelson-interactor 1 adapter protein, controls the abundance and localization of ABI1 protein isoforms in pancreatic cancer cells and promotes the relocalization of ABI1 from the cytoplasm to the periphery of migrating cells. Using splice-switching antisense oligonucleotides (AONs) we demonstrate the ABI1 ∆Ex9 isoform enhances cell migration. Together, our data identify a role for RBFOX2 in promoting PDAC progression through alternative splicing regulation.

Increased spatial coupling of integrin and collagen IV in the immunoresistant clear cell renal cell carcinoma tumor microenvironment.

Background: Immunotherapy (IO) has improved survival for patients with advanced clear cell renal cell carcinoma (ccRCC), but resistance to therapy develops in most patients. We use cellular-resolution spatial transcriptomics in patients with IO naïve and IO exposed primary ccRCC tumors to better understand IO resistance. Spatial molecular imaging (SMI) was obtained for tumor and adjacent stroma samples. Spatial gene set enrichment analysis (GSEA) and autocorrelation (coupling with high expression) of ligand-receptor transcript pairs were assessed. Multiplex immunofluorescence (mIF) validation was used for significant autocorrelative findings and the cancer genome atlas (TCGA) and the clinical proteomic tumor analysis consortium (CPTAC) databases were queried to assess bulk RNA expression and proteomic correlates. Results: 21 patient samples underwent SMI. Viable tumors following IO harbored more stromal CD8+ T cells and neutrophils than IO naïve tumors. YES1 was significantly upregulated in IO exposed tumor cells. The epithelial-mesenchymal transition pathway was enriched on spatial GSEA and the associated transcript pair COL4A1-ITGAV had significantly higher autocorrelation in the stroma. Fibroblasts, tumor cells, and endothelium had the relative highest expression. More integrin αV+ cells were seen in IO exposed stroma on mIF validation. Compared to other cancers in TCGA, ccRCC tumors have the highest expression of both COL4A1 and ITGAV. In CPTAC, collagen IV protein was more abundant in advanced stages of disease. Conclusions: On spatial transcriptomics, COL4A1 and ITGAV were more autocorrelated in IO-exposed stroma compared to IO-naïve tumors, with high expression amongst fibroblasts, tumor cells, and endothelium. Integrin represents a potential therapeutic target in IO treated ccRCC.

Brain metastasis-associated fibroblasts secrete fucosylated PVR/CD155 that induces breast cancer invasion.

Brain metastasis cancer-associated fibroblasts (bmCAFs) are emerging as crucial players in the development of breast cancer brain metastasis (BCBM), but our understanding of the underlying molecular mechanisms is limited. In this study, we aim to elucidate the pathological contributions of fucosylation (the post-translational modification of proteins by the dietary sugar L-fucose) to tumor-stromal interactions that drive the development of BCBM. Here, we report that patient-derived bmCAFs secrete high levels of polio virus receptor (PVR), which enhance the invasive capacity of BC cells. Mechanistically, we find that HIF1α transcriptionally upregulates fucosyltransferase 11, which fucosylates PVR, triggering its secretion from bmCAFs. Global phosphoproteomic analysis of BC cells followed by functional verification identifies cell-cell junction and actin cytoskeletal signaling as modulated by bmCAF-secreted, -fucosylated PVR. Our findings delineate a hypoxia- and fucosylation-regulated mechanism by which bmCAFs contribute to the invasiveness of BCBM in the brain.

Associations between prediagnostic aspirin use and ovarian tumor gene expression.

BACKGROUND: Aspirin use has been associated with reduced ovarian cancer risk, yet the underlying biological mechanisms are not fully understood. To gain mechanistic insights, we assessed the association between prediagnosis low and regular-dose aspirin use and gene expression profiles in ovarian tumors. METHODS: RNA sequencing was performed on high-grade serous, poorly differentiated, and high-grade endometrioid ovarian cancer tumors from the Nurses' Health Study (NHS), NHSII, and New England Case-Control Study (n = 92 cases for low, 153 cases for regular-dose aspirin). Linear regression identified differentially expressed genes associated with aspirin use, adjusted for birth decade and cohort. False discovery rates (FDR) were used to account for multiple testing and gene set enrichment analysis was used to identify biological pathways. RESULTS: No individual genes were significantly differentially expressed in ovarian tumors in low or regular-dose aspirin users accounting for multiple comparisons. However, current versus never use of low-dose aspirin was associated with upregulation of immune pathways (e.g., allograft rejection, FDR = 5.8 × 10-10 ; interferon-gamma response, FDR = 2.0 × 10-4 ) and downregulation of estrogen response pathways (e.g., estrogen response late, FDR = 4.9 × 10-8 ). Ovarian tumors from current regular aspirin users versus never users were also associated with upregulation in interferon pathways (FDR <1.5 × 10-4 ) and downregulation of multiple extracellular matrix (ECM) architecture pathways (e.g., ECM organization, 4.7 × 10-8 ). CONCLUSION: Our results suggest low and regular-dose aspirin may impair ovarian tumorigenesis in part via enhancing adaptive immune response and decreasing metastatic potential supporting the likely differential effects on ovarian carcinogenesis and progression by dose of aspirin.

An Assessment of the Penile Squamous Cell Carcinoma Surfaceome for Biomarker and Therapeutic Target Discovery.

Penile squamous cell carcinoma (PSCC) is a rare malignancy in most parts of the world and the underlying mechanisms of this disease have not been fully investigated. About 30-50% of cases are associated with high-risk human papillomavirus (HPV) infection, which may have prognostic value. When PSCC becomes resistant to upfront therapies there are limited options, thus further research is needed in this venue. The extracellular domain-facing protein profile on the cell surface (i.e., the surfaceome) is a key area for biomarker and drug target discovery. This research employs computational methods combined with cell line translatomic (n = 5) and RNA-seq transcriptomic data from patient-derived tumors (n = 18) to characterize the PSCC surfaceome, evaluate the composition dependency on HPV infection, and explore the prognostic impact of identified surfaceome candidates. Immunohistochemistry (IHC) was used to validate the localization of select surfaceome markers. This analysis characterized a diverse surfaceome within patient tumors with 25% and 18% of the surfaceome represented by the functional classes of receptors and transporters, respectively. Significant differences in protein classes were noted by HPV status, with the most change being seen in transporter proteins (25%). IHC confirmed the robust surface expression of select surfaceome targets in the top 85% of expression and a superfamily immunoglobulin protein called BSG/CD147 was prognostic of survival. This study provides the first description of the PSCC surfaceome and its relation to HPV infection and sets a foundation for novel biomarker and drug target discovery in this rare cancer.