Custom scoring based on ecological topology of gut microbiota associated with cancer immunotherapy outcome.

The gut microbiota influences the clinical responses of cancer patients to immunecheckpoint inhibitors (ICIs). However, there is no consensus definition of detrimental dysbiosis. Based on metagenomics (MG) sequencing of 245 non-small cell lung cancer (NSCLC) patient feces, we constructed species-level co-abundance networks that were clustered into species-interacting groups (SIGs) correlating with overall survival. Thirty-seven and forty-five MG species (MGSs) were associated with resistance (SIG1) and response (SIG2) to ICIs, respectively. When combined with the quantification of Akkermansia species, this procedure allowed a person-based calculation of a topological score (TOPOSCORE) that was validated in an additional 254 NSCLC patients and in 216 genitourinary cancer patients. Finally, this TOPOSCORE was translated into a 21-bacterial probe set-based qPCR scoring that was validated in a prospective cohort of NSCLC patients as well as in colorectal and melanoma patients. This approach could represent a dynamic diagnosis tool for intestinal dysbiosis to guide personalized microbiota-centered interventions.

Resurrection of endogenous retroviruses during aging reinforces senescence.

Whether and how certain transposable elements with viral origins, such as endogenous retroviruses (ERVs) dormant in our genomes, can become awakened and contribute to the aging process is largely unknown. In human senescent cells, we found that HERVK (HML-2), the most recently integrated human ERVs, are unlocked to transcribe viral genes and produce retrovirus-like particles (RVLPs). These HERVK RVLPs constitute a transmissible message to elicit senescence phenotypes in young cells, which can be blocked by neutralizing antibodies. The activation of ERVs was also observed in organs of aged primates and mice as well as in human tissues and serum from the elderly. Their repression alleviates cellular senescence and tissue degeneration and, to some extent, organismal aging. These findings indicate that the resurrection of ERVs is a hallmark and driving force of cellular senescence and tissue aging.

Proteogenomic analysis of chemo-refractory high-grade serous ovarian cancer.

To improve the understanding of chemo-refractory high-grade serous ovarian cancers (HGSOCs), we characterized the proteogenomic landscape of 242 (refractory and sensitive) HGSOCs, representing one discovery and two validation cohorts across two biospecimen types (formalin-fixed paraffin-embedded and frozen). We identified a 64-protein signature that predicts with high specificity a subset of HGSOCs refractory to initial platinum-based therapy and is validated in two independent patient cohorts. We detected significant association between lack of Ch17 loss of heterozygosity (LOH) and chemo-refractoriness. Based on pathway protein expression, we identified 5 clusters of HGSOC, which validated across two independent patient cohorts and patient-derived xenograft (PDX) models. These clusters may represent different mechanisms of refractoriness and implicate putative therapeutic vulnerabilities.

Endometriosis: Etiology, pathobiology, and therapeutic prospects.

Endometriosis is a common condition associated with infertility that causes chronic pain in many, but not all, women. It is defined by the presence of endometrial-like tissue outside the uterus. Although the cause and natural history of the disorder remain uncertain, hormonal, neurological, and immunological factors are all implicated in the mechanisms contributing to development of symptoms. Because definitive diagnosis requires surgery, there is often a long diagnostic delay after onset of symptoms. Current interventions for endometriosis have limited efficacy and unacceptable side effects/risks and are associated with high rates of symptom recurrence. Here, we review recent advances in our understanding of the etiology of endometriosis, discuss current diagnostic and treatment strategies, highlight current clinical trials, and consider how recent results offer new avenues for the identification of endometriosis biomarkers and the development of effective non-surgical therapies that are fertility-sparing.

Integrative Proteomic Characterization of Human Lung Adenocarcinoma.

Genomic studies of lung adenocarcinoma (LUAD) have advanced our understanding of the disease's biology and accelerated targeted therapy. However, the proteomic characteristics of LUAD remain poorly understood. We carried out a comprehensive proteomics analysis of 103 cases of LUAD in Chinese patients. Integrative analysis of proteome, phosphoproteome, transcriptome, and whole-exome sequencing data revealed cancer-associated characteristics, such as tumor-associated protein variants, distinct proteomics features, and clinical outcomes in patients at an early stage or with EGFR and TP53 mutations. Proteome-based stratification of LUAD revealed three subtypes (S-I, S-II, and S-III) related to different clinical and molecular features. Further, we nominated potential drug targets and validated the plasma protein level of HSP 90ß as a potential prognostic biomarker for LUAD in an independent cohort. Our integrative proteomics analysis enables a more comprehensive understanding of the molecular landscape of LUAD and offers an opportunity for more precise diagnosis and treatment.

Widespread and Functional RNA Circularization in Localized Prostate Cancer.

The cancer transcriptome is remarkably complex, including low-abundance transcripts, many not polyadenylated. To fully characterize the transcriptome of localized prostate cancer, we performed ultra-deep total RNA-seq on 144 tumors with rich clinical annotation. This revealed a linear transcriptomic subtype associated with the aggressive intraductal carcinoma sub-histology and a fusion profile that differentiates localized from metastatic disease. Analysis of back-splicing events showed widespread RNA circularization, with the average tumor expressing 7,232 circular RNAs (circRNAs). The degree of circRNA production was correlated to disease progression in multiple patient cohorts. Loss-of-function screening identified 11.3% of highly abundant circRNAs as essential for cell proliferation; for ∼90% of these, their parental linear transcripts were not essential. Individual circRNAs can have distinct functions, with circCSNK1G3 promoting cell growth by interacting with miR-181. These data advocate for adoption of ultra-deep RNA-seq without poly-A selection to interrogate both linear and circular transcriptomes.

Tumor-Induced Generation of Splenic Erythroblast-like Ter-Cells Promotes Tumor Progression.

Identifying tumor-induced leukocyte subsets and their derived circulating factors has been instrumental in understanding cancer as a systemic disease. Nevertheless, how primary tumor-induced non-leukocyte populations in distal organs contribute to systemic spread remains poorly defined. Here, we report one population of tumor-inducible, erythroblast-like cells (Ter-cells) deriving from megakaryocyte-erythroid progenitor cells with a unique Ter-119+CD45-CD71+ phenotype. Ter-cells are enriched in the enlarged spleen of hosts bearing advanced tumors and facilitate tumor progression by secreting neurotrophic factor artemin into the blood. Transforming growth factor ß (TGF-ß) and Smad3 activation are important in Ter-cell generation. In vivo blockade of Ter-cell-derived artemin inhibits hepatocellular carcinoma (HCC) growth, and artemin deficiency abolishes Ter-cells' tumor-promoting ability. We confirm the presence of splenic artemin-positive Ter-cells in human HCC patients and show that significantly elevated serum artemin correlates with poor prognosis. We propose that Ter-cells and the secreted artemin play important roles in cancer progression with prognostic and therapeutic implications.

Distinct immunological signatures discriminate severe COVID-19 from non-SARS-CoV-2-driven critical pneumonia.

Immune profiling of COVID-19 patients has identified numerous alterations in both innate and adaptive immunity. However, whether those changes are specific to SARS-CoV-2 or driven by a general inflammatory response shared across severely ill pneumonia patients remains unknown. Here, we compared the immune profile of severe COVID-19 with non-SARS-CoV-2 pneumonia ICU patients using longitudinal, high-dimensional single-cell spectral cytometry and algorithm-guided analysis. COVID-19 and non-SARS-CoV-2 pneumonia both showed increased emergency myelopoiesis and displayed features of adaptive immune paralysis. However, pathological immune signatures suggestive of T cell exhaustion were exclusive to COVID-19. The integration of single-cell profiling with a predicted binding capacity of SARS-CoV-2 peptides to the patients' HLA profile further linked the COVID-19 immunopathology to impaired virus recognition. Toward clinical translation, circulating NKT cell frequency was identified as a predictive biomarker for patient outcome. Our comparative immune map serves to delineate treatment strategies to interfere with the immunopathologic cascade exclusive to severe COVID-19.

Diapedesis-Induced Integrin Signaling via LFA-1 Facilitates Tissue Immunity by Inducing Intrinsic Complement C3 Expression in Immune Cells.

Intrinsic complement C3 activity is integral to human T helper type 1 (Th1) and cytotoxic T cell responses. Increased or decreased intracellular C3 results in autoimmunity and infections, respectively. The mechanisms regulating intracellular C3 expression remain undefined. We identified complement, including C3, as among the most significantly enriched biological pathway in tissue-occupying cells. We generated C3-reporter mice and confirmed that C3 expression was a defining feature of tissue-immune cells, including T cells and monocytes, occurred during transendothelial diapedesis, and depended on integrin lymphocyte-function-associated antigen 1 (LFA-1) signals. Immune cells from patients with leukocyte adhesion deficiency type 1 (LAD-1) had reduced C3 transcripts and diminished effector activities, which could be rescued proportionally by intracellular C3 provision. Conversely, increased C3 expression by T cells from arthritis patients correlated with disease severity. Our study defines integrins as key controllers of intracellular complement, demonstrates that perturbations in the LFA-1-C3-axis contribute to primary immunodeficiency, and identifies intracellular C3 as biomarker of severity in autoimmunity.

Functional implications of fumarate-induced cysteine succination.

Mutations in metabolic enzymes are associated with hereditary and sporadic forms of cancer. For example, loss-of-function mutations affecting fumarate hydratase (FH), the tricarboxylic acid (TCA) cycle enzyme, result in the accumulation of millimolar levels of fumarate that cause an aggressive form of kidney cancer. A distinct feature of fumarate is its ability to spontaneously react with thiol groups of cysteines in a chemical reaction termed succination. Although succination of a few proteins has been causally implicated in the molecular features of FH-deficient cancers, the stoichiometry, wider functional consequences, and contribution of succination to disease development remain largely unexplored. We discuss the functional implications of fumarate-induced succination in FH-deficient cells, the available methodologies, and the current challenges in studying this post-translational modification.

Tumor-neutrophil cross talk orchestrates the tumor microenvironment to determine the bladder cancer progression.

The immune landscape of bladder cancer progression is not fully understood, and effective therapies are lacking in advanced bladder cancer. Here, we visualized that bladder cancer cells recruited neutrophils by secreting interleukin-8 (IL-8); in turn, neutrophils played dual functions in bladder cancer, including hepatocyte growth factor (HGF) release and CCL3highPD-L1high super-immunosuppressive subset formation. Mechanistically, c-Fos was identified as the mediator of HGF up-regulating IL-8 transcription in bladder cancer cells, which was central to the positive feedback of neutrophil recruitment. Clinically, compared with serum IL-8, urine IL-8 was a better biomarker for bladder cancer prognosis and clinical benefit of immune checkpoint blockade (ICB). Additionally, targeting neutrophils or hepatocyte growth factor receptor (MET) signaling combined with ICB inhibited bladder cancer progression and boosted the antitumor effect of CD8+ T cells in mice. These findings reveal the mechanism by which tumor-neutrophil cross talk orchestrates the bladder cancer microenvironment and provide combination strategies, which may have broad impacts on patients suffering from malignancies enriched with neutrophils.

Antigen-specific age-related memory CD8 T cells induce and track Alzheimer's-like neurodegeneration.

Cerebral (Aß) plaque and (pTau) tangle deposition are hallmarks of Alzheimer's disease (AD), yet are insufficient to confer complete AD-like neurodegeneration experimentally. Factors acting upstream of Aß/pTau in AD remain unknown, but their identification could enable earlier diagnosis and more effective treatments. T cell abnormalities are emerging AD hallmarks, and CD8 T cells were recently found to mediate neurodegeneration downstream of tangle deposition in hereditary neurodegeneration models. The precise impact of T cells downstream of Aß/pTau, however, appears to vary depending on the animal model. Our prior work suggested that antigen-specific memory CD8 T ("hiT") cells act upstream of Aß/pTau after brain injury. Here, we examine whether hiT cells influence sporadic AD-like pathophysiology upstream of Aß/pTau. Examining neuropathology, gene expression, and behavior in our hiT mouse model we show that CD8 T cells induce plaque and tangle-like deposition, modulate AD-related genes, and ultimately result in progressive neurodegeneration with both gross and fine features of sporadic human AD. T cells required Perforin to initiate this pathophysiology, and IFNγ for most gene expression changes and progression to more widespread neurodegenerative disease. Analogous antigen-specific memory CD8 T cells were significantly elevated in the brains of human AD patients, and their loss from blood corresponded to sporadic AD and related cognitive decline better than plasma pTau-217, a promising AD biomarker candidate. We identify an age-related factor acting upstream of Aß/pTau to initiate AD-like pathophysiology, the mechanisms promoting its pathogenicity, and its relevance to human sporadic AD.

Targeting and monitoring ovarian cancer invasion with an RNAi and peptide delivery system.

RNA interference (RNAi) therapeutics are an emerging class of medicines that selectively target mRNA transcripts to silence protein production and combat disease. Despite the recent progress, a generalizable approach for monitoring the efficacy of RNAi therapeutics without invasive biopsy remains a challenge. Here, we describe the development of a self-reporting, theranostic nanoparticle that delivers siRNA to silence a protein that drives cancer progression while also monitoring the functional activity of its downstream targets. Our therapeutic target is the transcription factor SMARCE1, which was previously identified as a key driver of invasion in early-stage breast cancer. Using a doxycycline-inducible shRNA knockdown in OVCAR8 ovarian cancer cells both in vitro and in vivo, we demonstrate that SMARCE1 is a master regulator of genes encoding proinvasive proteases in a model of human ovarian cancer. We additionally map the peptide cleavage profiles of SMARCE1-regulated proteases so as to design a readout for downstream enzymatic activity. To demonstrate the therapeutic and diagnostic potential of our approach, we engineered self-assembled layer-by-layer nanoparticles that can encapsulate nucleic acid cargo and be decorated with peptide substrates that release a urinary reporter upon exposure to SMARCE1-related proteases. In an orthotopic ovarian cancer xenograft model, theranostic nanoparticles were able to knockdown SMARCE1 which was in turn reported through a reduction in protease-activated urinary reporters. These LBL nanoparticles both silence gene products by delivering siRNA and noninvasively report on downstream target activity by delivering synthetic biomarkers to sites of disease, enabling dose-finding studies as well as longitudinal assessments of efficacy.

Oncofetal IGF2BP3-mediated control of microRNA structural diversity in the malignancy of early-stage lung adenocarcinoma.

The nature of microRNA (miRNA) dysfunction in carcinogenesis remains controversial because of the complex connection between miRNA structural diversity and biological processes. Here, we found that oncofetal IGF2BP3 regulates the selective production of a subset of 3'-isoforms (3'-isomiRs), including miR-21-5p and Let-7 family, which induces significant changes in their cellular seed occupancy and structural components, establishing a cancer-specific gene expression profile. The D-score, reflecting dominant production of a representative miR-21-5p+C (a 3'-isomiR), discriminated between clinical early-stage lung adenocarcinoma (LUAD) cases with low and high recurrence risks, and was associated with molecular features of cell cycle progression, epithelial-mesenchymal transition pressure, and immune evasion. We found that IGF2BP3 controls the production of miR-21-5p+C by directing the nuclear Drosha complex to select the cleavage site. IGF2BP3 was also involved in the production of 3'-isomiRs of miR-425-5p and miR-454-3p. IGF2BP3-regulated these three miRNAs are suggested to be associated with the regulation of p53, TGF-ß, and TNF pathways in LUAD. Knockdown of IGF2BP3 also induced a selective upregulation of Let-7 3'-isomiRs, leading to increased cellular Let-7 seed occupancy and broad repression of its target genes encoding cell cycle regulators. The D-score is an index that reflects this cellular situation. Our results suggest that the aberrant regulation of miRNA structural diversity is a critical component for controlling cellular networks, thus supporting the establishment of a malignant gene expression profile in early stage LUAD.

Accurate estimation of biological age and its application in disease prediction using a multimodal image Transformer system.

Aging in an individual refers to the temporal change, mostly decline, in the body's ability to meet physiological demands. Biological age (BA) is a biomarker of chronological aging and can be used to stratify populations to predict certain age-related chronic diseases. BA can be predicted from biomedical features such as brain MRI, retinal, or facial images, but the inherent heterogeneity in the aging process limits the usefulness of BA predicted from individual body systems. In this paper, we developed a multimodal Transformer-based architecture with cross-attention which was able to combine facial, tongue, and retinal images to estimate BA. We trained our model using facial, tongue, and retinal images from 11,223 healthy subjects and demonstrated that using a fusion of the three image modalities achieved the most accurate BA predictions. We validated our approach on a test population of 2,840 individuals with six chronic diseases and obtained significant difference between chronological age and BA (AgeDiff) than that of healthy subjects. We showed that AgeDiff has the potential to be utilized as a standalone biomarker or conjunctively alongside other known factors for risk stratification and progression prediction of chronic diseases. Our results therefore highlight the feasibility of using multimodal images to estimate and interrogate the aging process.

Autoimmunity in immune checkpoint inhibitor-induced immune-related adverse events: A focus on autoimmune skin toxicity and pneumonitis.

Immune checkpoint inhibitors (ICIs) have revolutionized cancer therapy. However, their use is frequently associated with immune-related adverse events (irAEs) potentially affecting any organ. The mechanisms mediating such irAEs remain poorly understood and biomarkers to predict the development of irAEs are lacking. Growing evidence shows the importance of self-antigens in mediating irAEs during ICI therapy, in particular the well-described melanocyte differentiation antigens in melanoma patients. This review will focus on two novel classes of self-antigens involved in mediating autoimmune skin toxicity and pneumonitis in non-small cell lung cancer patients treated with immunotherapy. T cells specific for these self-antigens are thought to not only mediate irAEs but are thought to simultaneously mediate anti-tumor responses and are therefore associated with both autoimmune toxicity and response to ICI therapy. We further discuss emerging cellular and proteomic immune signatures of irAEs that may serve as biomarkers to help predict which patients are at higher risk of developing these irAEs. The determination of new tumor antigens involved in ICI therapy and the identification of related biomarkers brings us a step forward in the mechanistic understanding of ICIs and will help to monitor patients at higher risk of developing irAEs. Lastly, we discuss the current challenges in collecting research samples for the study of ICI-related mechanisms and in distinguishing between immune signatures of response and those of irAEs.

High-Sensitivity Cardiac Troponin Assays: Ready for Prime Time!

Rapid and accurate triage of patients presenting with chest pain to an emergency department (ED) is critical to prevent ED overcrowding and unnecessary resource use in individuals at low risk of acute myocardial infarction (AMI) and to efficiently and effectively guide patients at high risk to definite therapy. The use of biomarkers for rule-out or rule-in of suspected AMI has evolved substantially over the last several decades. Previously well-established biomarkers have been replaced by cardiac troponin (cTn). High-sensitivity cTn (hs-cTn) assays represent the newest generation of cTn assays and offer tremendous advantages, including improved sensitivity and precision. Still, implementation of these assays in the United States lags behind several other areas of the world. Within this educational review, we discuss the evolution of biomarker testing for detection of myocardial injury, address the specifics of hs-cTn assays and their recommended use within triage algorithms, and highlight potential challenges in their use. Ultimately, we focus on implementation strategies for hs-cTn assays, as they are now clearly ready for prime time.

CDHu40: a novel marker gene set of neuroendocrine prostate cancer.

Prostate cancer (PCa) is the most prevalent cancer affecting American men. Castration-resistant prostate cancer (CRPC) can emerge during hormone therapy for PCa, manifesting with elevated serum prostate-specific antigen levels, continued disease progression, and/or metastasis to the new sites, resulting in a poor prognosis. A subset of CRPC patients shows a neuroendocrine (NE) phenotype, signifying reduced or no reliance on androgen receptor signaling and a particularly unfavorable prognosis. In this study, we incorporated computational approaches based on both gene expression profiles and protein-protein interaction networks. We identified 500 potential marker genes, which are significantly enriched in cell cycle and neuronal processes. The top 40 candidates, collectively named CDHu40, demonstrated superior performance in distinguishing NE PCa (NEPC) and non-NEPC samples based on gene expression profiles. CDHu40 outperformed most of the other published marker sets, excelling particularly at the prognostic level. Notably, some marker genes in CDHu40, absent in the other marker sets, have been reported to be associated with NEPC in the literature, such as DDC, FOLH1, BEX1, MAST1, and CACNA1A. Importantly, elevated CDHu40 scores derived from our predictive model showed a robust correlation with unfavorable survival outcomes in patients, indicating the potential of the CDHu40 score as a promising indicator for predicting the survival prognosis of those patients with the NE phenotype. Motif enrichment analysis on the top candidates suggests that REST and E2F6 may serve as key regulators in the NEPC progression.

Performance assessment of computational tools to detect microsatellite instability.

Microsatellite instability (MSI) is a phenomenon seen in several cancer types, which can be used as a biomarker to help guide immune checkpoint inhibitor treatment. To facilitate this, researchers have developed computational tools to categorize samples as having high microsatellite instability, or as being microsatellite stable using next-generation sequencing data. Most of these tools were published with unclear scope and usage, and they have yet to be independently benchmarked. To address these issues, we assessed the performance of eight leading MSI tools across several unique datasets that encompass a wide variety of sequencing methods. While we were able to replicate the original findings of each tool on whole exome sequencing data, most tools had worse receiver operating characteristic and precision-recall area under the curve values on whole genome sequencing data. We also found that they lacked agreement with one another and with commercial MSI software on gene panel data, and that optimal threshold cut-offs vary by sequencing type. Lastly, we tested tools made specifically for RNA sequencing data and found they were outperformed by tools designed for use with DNA sequencing data. Out of all, two tools (MSIsensor2, MANTIS) performed well across nearly all datasets, but when all datasets were combined, their precision decreased. Our results caution that MSI tools can have much lower performance on datasets other than those on which they were originally evaluated, and in the case of RNA sequencing tools, can even perform poorly on the type of data for which they were created.

TG468: a text graph convolutional network for predicting clinical response to immune checkpoint inhibitor therapy.

Enhancing cancer treatment efficacy remains a significant challenge in human health. Immunotherapy has witnessed considerable success in recent years as a treatment for tumors. However, due to the heterogeneity of diseases, only a fraction of patients exhibit a positive response to immune checkpoint inhibitor (ICI) therapy. Various single-gene-based biomarkers and tumor mutational burden (TMB) have been proposed for predicting clinical responses to ICI; however, their predictive ability is limited. We propose the utilization of the Text Graph Convolutional Network (GCN) method to comprehensively assess the impact of multiple genes, aiming to improve the predictive capability for ICI response. We developed TG468, a Text GCN model framing drug response prediction as a text classification task. By combining natural language processing (NLP) and graph neural network techniques, TG468 effectively handles sparse and high-dimensional exome sequencing data. As a result, TG468 can distinguish survival time for patients who received ICI therapy and outperforms single gene biomarkers, TMB and some classical machine learning models. Additionally, TG468's prediction results facilitate the identification of immune status differences among specific patient types in the Cancer Genome Atlas dataset, providing a rationale for the model's predictions. Our approach represents a pioneering use of a GCN model to analyze exome data in patients undergoing ICI therapy and offers inspiration for future research using NLP technology to analyze exome sequencing data.