The intrinsic substrate specificity of the human tyrosine kinome.

Phosphorylation of proteins on tyrosine (Tyr) residues evolved in metazoan organisms as a mechanism of coordinating tissue growth1. Multicellular eukaryotes typically have more than 50 distinct protein Tyr kinases that catalyse the phosphorylation of thousands of Tyr residues throughout the proteome1-3. How a given Tyr kinase can phosphorylate a specific subset of proteins at unique Tyr sites is only partially understood4-7. Here we used combinatorial peptide arrays to profile the substrate sequence specificity of all human Tyr kinases. Globally, the Tyr kinases demonstrate considerable diversity in optimal patterns of residues surrounding the site of phosphorylation, revealing the functional organization of the human Tyr kinome by substrate motif preference. Using this information, Tyr kinases that are most compatible with phosphorylating any Tyr site can be identified. Analysis of mass spectrometry phosphoproteomic datasets using this compendium of kinase specificities accurately identifies specific Tyr kinases that are dysregulated in cells after stimulation with growth factors, treatment with anti-cancer drugs or expression of oncogenic variants. Furthermore, the topology of known Tyr signalling networks naturally emerged from a comparison of the sequence specificities of the Tyr kinases and the SH2 phosphotyrosine (pTyr)-binding domains. Finally we show that the intrinsic substrate specificity of Tyr kinases has remained fundamentally unchanged from worms to humans, suggesting that the fidelity between Tyr kinases and their protein substrate sequences has been maintained across hundreds of millions of years of evolution.

MGMT ProFWise: Unlocking a New Application for Combined Feature Selection and the Rank-Based Weighting Method to Link MGMT Methylation Status to Serum Protein Expression in Patients with Glioblastoma.

Glioblastoma (GBM) is a fatal brain tumor with limited treatment options. O6-methylguanine-DNA-methyltransferase (MGMT) promoter methylation status is the central molecular biomarker linked to both the response to temozolomide, the standard chemotherapy drug employed for GBM, and to patient survival. However, MGMT status is captured on tumor tissue which, given the difficulty in acquisition, limits the use of this molecular feature for treatment monitoring. MGMT protein expression levels may offer additional insights into the mechanistic understanding of MGMT but, currently, they correlate poorly to promoter methylation. The difficulty of acquiring tumor tissue for MGMT testing drives the need for non-invasive methods to predict MGMT status. Feature selection aims to identify the most informative features to build accurate and interpretable prediction models. This study explores the new application of a combined feature selection (i.e., LASSO and mRMR) and the rank-based weighting method (i.e., MGMT ProFWise) to non-invasively link MGMT promoter methylation status and serum protein expression in patients with GBM. Our method provides promising results, reducing dimensionality (by more than 95%) when employed on two large-scale proteomic datasets (7k SomaScan® panel and CPTAC) for all our analyses. The computational results indicate that the proposed approach provides 14 shared serum biomarkers that may be helpful for diagnostic, prognostic, and/or predictive operations for GBM-related processes, given further validation.

How Artificial Intelligence Unravels the Complex Web of Cancer Drug Response.

The intersection of precision medicine and artificial intelligence (AI) holds profound implications for cancer treatment, with the potential to significantly advance our understanding of drug responses based on the intricate architecture of tumor cells. A recent study by Park and colleagues titled "A deep learning model of tumor cell architecture elucidates response and resistance to CDK4/6 inhibitors," epitomizes this intersection by leveraging an interpretable deep learning model grounded in a comprehensive map of multiprotein assemblies in cancer, known as Nested Systems in Tumors (NeST). This study not only elucidates mechanisms underlying the response to CDK4/6 inhibitors in breast cancer therapy but also highlights the critical role of model interpretability leading to new mechanistic insights.

Benchmarking multi-ancestry prostate cancer polygenic risk scores in a real-world cohort.

Prostate cancer is a heritable disease with ancestry-biased incidence and mortality. Polygenic risk scores (PRSs) offer promising advancements in predicting disease risk, including prostate cancer. While their accuracy continues to improve, research aimed at enhancing their effectiveness within African and Asian populations remains key for equitable use. Recent algorithmic developments for PRS derivation have resulted in improved pan-ancestral risk prediction for several diseases. In this study, we benchmark the predictive power of six widely used PRS derivation algorithms, including four of which adjust for ancestry, against prostate cancer cases and controls from the UK Biobank and All of Us cohorts. We find modest improvement in discriminatory ability when compared with a simple method that prioritizes variants, clumping, and published polygenic risk scores. Our findings underscore the importance of improving upon risk prediction algorithms and the sampling of diverse cohorts.

Rewiring Endothelial Sphingolipid Metabolism to Favor S1P Over Ceramide Protects From Coronary Atherosclerosis.

BACKGROUND: Growing evidence correlated changes in bioactive sphingolipids, particularly S1P (sphingosine-1-phosphate) and ceramides, with coronary artery diseases. Furthermore, specific plasma ceramide species can predict major cardiovascular events. Dysfunction of the endothelium lining lesion-prone areas plays a pivotal role in atherosclerosis. Yet, how sphingolipid metabolism and signaling change and contribute to endothelial dysfunction and atherosclerosis remain poorly understood. METHODS: We used an established model of coronary atherosclerosis in mice, combined with sphingolipidomics, RNA-sequencing, flow cytometry, and immunostaining to investigate the contribution of sphingolipid metabolism and signaling to endothelial cell (EC) activation and dysfunction. RESULTS: We demonstrated that hemodynamic stress induced an early metabolic rewiring towards endothelial sphingolipid de novo biosynthesis, favoring S1P signaling over ceramides as a protective response. This finding is a paradigm shift from the current belief that ceramide accrual contributes to endothelial dysfunction. The enzyme SPT (serine palmitoyltransferase) commences de novo biosynthesis of sphingolipids and is inhibited by NOGO-B (reticulon-4B), an ER membrane protein. Here, we showed that NOGO-B is upregulated by hemodynamic stress in myocardial EC of ApoE-/- mice and is expressed in the endothelium lining coronary lesions in mice and humans. We demonstrated that mice lacking NOGO-B specifically in EC (Nogo-A/BECKOApoE-/-) were resistant to coronary atherosclerosis development and progression, and mortality. Fibrous cap thickness was significantly increased in Nogo-A/BECKOApoE-/- mice and correlated with reduced necrotic core and macrophage infiltration. Mechanistically, the deletion of NOGO-B in EC sustained the rewiring of sphingolipid metabolism towards S1P, imparting an atheroprotective endothelial transcriptional signature. CONCLUSIONS: These data demonstrated that hemodynamic stress induced a protective rewiring of sphingolipid metabolism, favoring S1P over ceramide. NOGO-B deletion sustained the rewiring of sphingolipid metabolism toward S1P protecting EC from activation under hemodynamic stress and refraining coronary atherosclerosis. These findings also set forth the foundation for sphingolipid-based therapeutics to limit atheroprogression.

Tumor-Associated Lymphocytes and Breast Cancer Survival in Black and White Women.

This case series evaluates whether differences in immune filtration are associated with breast cancer risk in Black vs White women.

The evolution of metastatic upper tract urothelial carcinoma through genomic-transcriptomic and single-cell protein markers analysis.

The molecular characteristics of metastatic upper tract urothelial carcinoma (UTUC) are not well understood, and there is a lack of knowledge regarding the genomic and transcriptomic differences between primary and metastatic UTUC. To address these gaps, we integrate whole-exome sequencing, RNA sequencing, and Imaging Mass Cytometry using lanthanide metal-conjugated antibodies of 44 tumor samples from 28 patients with high-grade primary and metastatic UTUC. We perform a spatially-resolved single-cell analysis of cancer, immune, and stromal cells to understand the evolution of primary to metastatic UTUC. We discover that actionable genomic alterations are frequently discordant between primary and metastatic UTUC tumors in the same patient. In contrast, molecular subtype membership and immune depletion signature are stable across primary and matched metastatic UTUC. Molecular and immune subtypes are consistent between bulk RNA-sequencing and mass cytometry of protein markers from 340,798 single cells. Molecular subtypes at the single-cell level are highly conserved between primary and metastatic UTUC tumors within the same patient.

The nuclear factor ID3 endows macrophages with a potent anti-tumour activity.

Macrophage activation is controlled by a balance between activating and inhibitory receptors1-7, which protect normal tissues from excessive damage during infection8,9 but promote tumour growth and metastasis in cancer7,10. Here we report that the Kupffer cell lineage-determining factor ID3 controls this balance and selectively endows Kupffer cells with the ability to phagocytose live tumour cells and orchestrate the recruitment, proliferation and activation of natural killer and CD8 T lymphoid effector cells in the liver to restrict the growth of a variety of tumours. ID3 shifts the macrophage inhibitory/activating receptor balance to promote the phagocytic and lymphoid response, at least in part by buffering the binding of the transcription factors ELK1 and E2A at the SIRPA locus. Furthermore, loss- and gain-of-function experiments demonstrate that ID3 is sufficient to confer this potent anti-tumour activity to mouse bone-marrow-derived macrophages and human induced pluripotent stem-cell-derived macrophages. Expression of ID3 is therefore necessary and sufficient to endow macrophages with the ability to form an efficient anti-tumour niche, which could be harnessed for cell therapy in cancer.

Whole-Genome Sequencing Analysis of Male Breast Cancer Unveils Novel Structural Events and Potential Therapeutic Targets.

The molecular characterization of male breast cancer (MaBC) has received limited attention in research, mostly because of its low incidence rate, accounting for only 0.5% to 1% of all reported cases of breast cancer each year. Managing MaBC presents significant challenges, with most treatment protocols being adapted from those developed for female breast cancer. Utilizing whole-genome sequencing (WGS) and state-of-the-art analyses, the genomic features of 10 MaBC cases (n = 10) were delineated and correlated with clinical and histopathologic characteristics. Using fluorescence in situ hybridization, an additional cohort of 18 patients was interrogated to supplement WGS findings. The genomic landscape of MaBC uncovered significant genetic alterations that could influence diagnosis and treatment. We found common somatic mutations in key driver genes, such as FAT1, GATA3, SMARCA4, and ARID2. Our study also mapped out structural variants that impact cancer-associated genes, such as ARID1A, ESR1, GATA3, NTRK1, and NF1. Using a WGS-based classifier, homologous recombination deficiency (HRD) was identified in 2 cases, both presenting with deleterious variants in BRCA2. Noteworthy was the observation of FGFR1 amplification in 21% of cases. Altogether, we identified at least 1 potential therapeutic target in 8 of the 10 cases, including high tumor mutational burden, FGFR1 amplification, and HRD. Our study is the first WGS characterization of MaBC, which uncovered potentially relevant variants, including structural events in cancer genes, HRD signatures, and germline pathogenic mutations. Our results demonstrate unique genetic markers and potential treatment targets in MaBC, thereby underlining the necessity of tailoring treatment strategies for this understudied patient population. These WGS-based findings add to the growing knowledge of MaBC genomics and highlight the need to expand research on this type of cancer.

Voice as an AI Biomarker of Health-Introducing Audiomics.

This Viewpoint discusses the need to create standards for audiomics to identify unique audio biomarkers of health and disease­now possible because of more efficient voice data analysis available through the use of artificial intelligence (AI)­and to improve patient care.

A microglia clonal inflammatory disorder in Alzheimer's Disease.

Somatic genetic heterogeneity resulting from post-zygotic DNA mutations is widespread in human tissues and can cause diseases, however few studies have investigated its role in neurodegenerative processes such as Alzheimer's Disease (AD). Here we report the selective enrichment of microglia clones carrying pathogenic variants, that are not present in neuronal, glia/stromal cells, or blood, from patients with AD in comparison to age-matched controls. Notably, microglia-specific AD-associated variants preferentially target the MAPK pathway, including recurrent CBL ring-domain mutations. These variants activate ERK and drive a microglia transcriptional program characterized by a strong neuro-inflammatory response, both in vitro and in patients. Although the natural history of AD-associated microglial clones is difficult to establish in human, microglial expression of a MAPK pathway activating variant was previously shown to cause neurodegeneration in mice, suggesting that AD-associated neuroinflammatory microglial clones may contribute to the neurodegenerative process in patients.

Cysteine induces mitochondrial reductive stress in glioblastoma through hydrogen peroxide production.

Glucose and amino acid metabolism are critical for glioblastoma (GBM) growth, but little is known about the specific metabolic alterations in GBM that are targetable with FDA-approved compounds. To investigate tumor metabolism signatures unique to GBM, we interrogated The Cancer Genome Atlas for alterations in glucose and amino acid signatures in GBM relative to other human cancers and found that GBM exhibits the highest levels of cysteine and methionine pathway gene expression of 32 human cancers. Treatment of patient-derived GBM cells with the FDA-approved single cysteine compound N-acetylcysteine (NAC) reduced GBM cell growth and mitochondrial oxygen consumption, which was worsened by glucose starvation. Normal brain cells and other cancer cells showed no response to NAC. Mechanistic experiments revealed that cysteine compounds induce rapid mitochondrial H2O2 production and reductive stress in GBM cells, an effect blocked by oxidized glutathione, thioredoxin, and redox enzyme overexpression. From analysis of the clinical proteomic tumor analysis consortium (CPTAC) database, we found that GBM cells exhibit lower expression of mitochondrial redox enzymes than four other cancers whose proteomic data are available in CPTAC. Knockdown of mitochondrial thioredoxin-2 in lung cancer cells induced NAC susceptibility, indicating the importance of mitochondrial redox enzyme expression in mitigating reductive stress. Intraperitoneal treatment of mice bearing orthotopic GBM xenografts with a two-cysteine peptide induced H2O2 in brain tumors in vivo. These findings indicate that GBM is uniquely susceptible to NAC-driven reductive stress and could synergize with glucose-lowering treatments for GBM.

A signature of enhanced proliferation associated with response and survival to anti-PD-L1 therapy in early-stage non-small cell lung cancer.

In early-stage non-small cell lung cancer, the combination of neoadjuvant anti-PD-L1 and subablative stereotactic body radiation therapy (SBRT) is associated with higher rates of major pathologic response compared to anti-PD-L1 alone. Here, we identify a 140-gene set, enriched in genes characteristic of highly proliferating cells, associated with response to the dual therapy. Analysis of on-treatment transcriptome data indicate roles for T and B cells in response. The 140-gene set is associated with disease-free survival when applied to the combined trial arms. This 140-gene set identifies a subclass of tumors in all 7 of The Cancer Genome Atlas tumor types examined. Worse survival is associated with the 140-gene signature in 5 of these tumor types. Collectively, our data support that this 140-gene set, discovered in association with response to combined anti-PD-L1 and SBRT, identifies a clinically aggressive subclass of solid tumors that may be more likely to respond to immunotherapies.

Patient-derived tumor organoids with p53 mutations, and not wild-type p53, are sensitive to synergistic combination PARP inhibitor treatment.

Poly (ADP-ribose) polymerase inhibitors (PARPi) are used for patients with BRCA1/2 mutations, but patients with other mutations may benefit from PARPi treatment. Another mutation that is present in more cancers than BRCA1/2 is mutation to the TP53 gene. In 2D breast cancer cell lines, mutant p53 (mtp53) proteins tightly associate with replicating DNA and Poly (ADP-ribose) polymerase (PARP) protein. Combination drug treatment with the alkylating agent temozolomide and the PARPi talazoparib kills mtp53 expressing 2D grown breast cancer cell lines. We evaluated the sensitivity to the combination of temozolomide plus PARPi talazoparib treatment to breast and lung cancer patient-derived tumor organoids (PDTOs). The combination of the two drugs was synergistic for a cytotoxic response in PDTOs with mtp53 but not for PDTOs with wtp53. The combination of talazoparib and temozolomide induced more DNA double-strand breaks in mtp53 expressing organoids than in wild-type p53 expressing organoids as shown by increased γ-H2AX protein expression. Moreover, breast cancer tissue microarrays (TMAs) showed a positive correlation between stable p53 and high PARP1 expression in sub-groups of breast cancers, which may indicate sub-classes of breast cancers sensitive to PARPi therapy. These results suggest that mtp53 could be a biomarker to predict response to the combination of PARPi talazoparib-temozolomide treatment.

Noninvasive Detection of Neuroendocrine Prostate Cancer through Targeted Cell-free DNA Methylation.

Castration-resistant prostate cancer (CRPC) is a heterogeneous disease associated with phenotypic subtypes that drive therapy response and outcome differences. Histologic transformation to castration-resistant neuroendocrine prostate cancer (CRPC-NE) is associated with distinct epigenetic alterations, including changes in DNA methylation. The current diagnosis of CRPC-NE is challenging and relies on metastatic biopsy. We developed a targeted DNA methylation assay to detect CRPC-NE using plasma cell-free DNA (cfDNA). The assay quantifies tumor content and provides a phenotype evidence score that captures diverse CRPC phenotypes, leveraging regions to inform transcriptional state. We tested the design in independent clinical cohorts (n = 222 plasma samples) and qualified it achieving an AUC > 0.93 for detecting pathology-confirmed CRPC-NE (n = 136). Methylation-defined cfDNA tumor content was associated with clinical outcomes in two prospective phase II clinical trials geared towards aggressive variant CRPC and CRPC-NE. These data support the application of targeted DNA methylation for CRPC-NE detection and patient stratification. SIGNIFICANCE: Neuroendocrine prostate cancer is an aggressive subtype of treatment-resistant prostate cancer. Early detection is important, but the diagnosis currently relies on metastatic biopsy. We describe the development and validation of a plasma cell-free DNA targeted methylation panel that can quantify tumor fraction and identify patients with neuroendocrine prostate cancer noninvasively. This article is featured in Selected Articles from This Issue, p. 384.

A deep learning pipeline for automated classification of vocal fold polyps in flexible laryngoscopy.

PURPOSE: To develop and validate a deep learning model for distinguishing healthy vocal folds (HVF) and vocal fold polyps (VFP) on laryngoscopy videos, while demonstrating the ability of a previously developed informative frame classifier in facilitating deep learning development. METHODS: Following retrospective extraction of image frames from 52 HVF and 77 unilateral VFP videos, two researchers manually labeled each frame as informative or uninformative. A previously developed informative frame classifier was used to extract informative frames from the same video set. Both sets of videos were independently divided into training (60%), validation (20%), and test (20%) by patient. Machine-labeled frames were independently verified by two researchers to assess the precision of the informative frame classifier. Two models, pre-trained on ResNet18, were trained to classify frames as containing HVF or VFP. The accuracy of the polyp classifier trained on machine-labeled frames was compared to that of the classifier trained on human-labeled frames. The performance was measured by accuracy and area under the receiver operating characteristic curve (AUROC). RESULTS: When evaluated on a hold-out test set, the polyp classifier trained on machine-labeled frames achieved an accuracy of 85% and AUROC of 0.84, whereas the classifier trained on human-labeled frames achieved an accuracy of 69% and AUROC of 0.66. CONCLUSION: An accurate deep learning classifier for vocal fold polyp identification was developed and validated with the assistance of a peer-reviewed informative frame classifier for dataset assembly. The classifier trained on machine-labeled frames demonstrates improved performance compared to the classifier trained on human-labeled frames.

NIPBL::NACC1 Fusion Hepatic Carcinoma.

Several reports describing a rare primary liver tumor with histologic features reminiscent of follicular thyroid neoplasms have been published under a variety of descriptive terms including thyroid-like, solid tubulocystic, and cholangioblastic cholangiocarcinoma. Although these tumors are considered to represent histologic variants, they lack classic features of cholangiocarcinoma and have unique characteristics, namely immunoreactivity for inhibin and NIPBL::NACC1 fusions. The purpose of this study is to present clinicopathologic and molecular data for a large series of these tumors to better understand their pathogenesis. We identified 11 hepatic tumors with these features. Immunohistochemical and NACC1 and NIPBL fluorescence in situ hybridization assays were performed on all cases. Four cases had available material for whole-genome sequencing (WGS) analysis. Most patients were adult women (mean age: 42 y) who presented with abdominal pain and large hepatic masses (mean size: 14 cm). Ten patients had no known liver disease. Of the patients with follow-up information, 3/9 (33%) pursued aggressive behavior. All tumors were composed of bland cuboidal cells with follicular and solid/trabecular growth patterns in various combinations, were immunoreactive for inhibin, showed albumin mRNA by in situ hybridization, and harbored the NIPBL::NACC1 fusion by fluorescence in situ hybridization. WGS corroborated the presence of the fusion in all 4 tested cases, high tumor mutational burden in 2 cases, and over 30 structural variants per case in 3 sequenced tumors. The cases lacked mutations typical of conventional intrahepatic cholangiocarcinoma. In this report, we describe the largest series of primary inhibin-positive hepatic neoplasms harboring a NIPBL::NACC1 fusion and the first WGS analysis of these tumors. We propose to name this neoplasm NIPBL:NACC1 fusion hepatic carcinoma.

Transcriptomic signatures of chronic active antibody-mediated rejection deciphered by RNA sequencing of human kidney allografts.

Natural killer (NK) cells mediate spontaneous cell-mediated cytotoxicity and antibody-dependent cell-mediated cytotoxicity. This dual functionality could enable their participation in chronic active antibody-mediated rejection (CA-ABMR). Earlier microarray profiling studies have not subcategorized antibody-mediated rejection into CA-ABMR and active-ABMR, and the gene expression pattern of CA-ABMR has not been compared with that of T cell-mediated rejection (TCMR). To fill these gaps, we RNA sequenced human kidney allograft biopsies categorized as CA-ABMR, active-ABMR, TCMR, or No Rejection (NR). Among the 15,910 genes identified in the biopsies, 60, 114, and 231 genes were uniquely overexpressed in CA-ABMR, TCMR, and active-ABMR, respectively; compared to NR, 50 genes were shared between CA-ABMR and active-ABMR, and 164 genes between CA-ABMR and TCMR. The overexpressed genes were annotated to NK cells and T cells in CA-ABMR and TCMR, and to neutrophils and monocytes in active-ABMR. The NK cell cytotoxicity and allograft rejection pathways were enriched in CA-ABMR. Genes encoding perforin, granzymes, and death receptor were overexpressed in CA-ABMR versus active-ABMR but not compared to TCMR. NK cell cytotoxicity pathway gene set variation analysis score was higher in CA-ABMR compared to active-ABMR but not in TCMR. Principal component analysis of the deconvolved immune cellular transcriptomes separated CA-ABMR and TCMR from active-ABMR and NR. Immunohistochemistry of kidney allograft biopsies validated a higher proportion of CD56+ NK cells in CA-ABMR than in active-ABMR. Thus, CA-ABMR was exemplified by the overexpression of the NK cell cytotoxicity pathway gene set and, surprisingly, molecularly more like TCMR than active-ABMR.

The Landscape of US and Global Rare Tumor Research Programs: A Systematic Review.

Rare cancers and other rare nonmalignant tumors comprise 25% of all cancer diagnoses and account for 25% of all cancer deaths. They are difficult to study due to many factors, including infrequent occurrence, lack of a universal infrastructure for data and/or tissue collection, and a paucity of disease models to test potential treatments. For each individual rare cancer, the limited number of diagnosed cases makes it difficult to recruit sufficient patients for clinical studies, and rare cancer research studies are often siloed. As a result, progress has been slow for many of these cancers. While rare cancer research efforts have increased over time, the breadth of the research landscape is not known. A recent literature search revealed a sharp increase in rare tumor, and rare cancer publications began in the early 2000s. To identify rare cancer research efforts being conducted in the US and globally, we conducted an online search of rare tumor/rare cancer research programs and identified 76 programs. To gain a deeper understanding of these programs, we composed and conducted a survey to ask programs for details about their research efforts. Of the 42 programs contacted to complete the survey, 23 programs responded. Survey results show most programs are collecting clinical data, molecular data, and biospecimens, and many are conducting molecular analyses. This landscape analysis demonstrates that multiple rare cancer research efforts are ongoing, and the rare cancer community may benefit from collaboration among stakeholders to accelerate research and improve patient outcomes.