Machine Learning Prediction Model for Neutrophil Recovery after Unrelated Cord Blood Transplantation.

Delayed neutrophil recovery is an important limitation to the administration of cord blood transplantation (CBT) and leaves the recipient vulnerable to life-threatening infection and increases the risk of other complications. A predictive model for neutrophil recovery after single-unit CBT was developed by using a machine learning method, which can handle large and complex datasets, allowing for the analysis of massive amounts of information to uncover patterns and make accurate predictions. Japanese registry data, the largest real-world dataset of CBT, was selected as the data source. Ninety-eight variables with observed values for >80% of the subjects known at the time of CBT were selected. Model building was performed with a competing risk regression model with lasso penalty. Prediction accuracy of the models was evaluated by calculating the area under the receiver operating characteristic curve (AUC) using a test dataset. The primary outcome was neutrophil recovery at day (D) 28, with recovery at D14 and D42 analyzed as secondary outcomes. The final cord blood engraftment prediction (CBEP) models included 2991 single-unit CBT recipients with acute leukemia. The median AUC of a D28-CBEP lasso regression model run 100 times was .74, and those for D14 and D42 were .88 and .68, respectively. The predictivity of the D28-CBEP model was higher than that of 4 different legacy models constructed separately. A highly predictive model for neutrophil recovery by 28 days after CBT was constructed using machine learning techniques; however, identification of significant risk factors was insufficient for outcome prediction for an individual patient, which is necessary for improving therapeutic outcomes. Notably, the prediction accuracy for post-transplantation D14, D28, and D42 decreased, and the model became more complex with more associated factors with increased time after transplantation.

KMT2C expression and DNA homologous recombination repair factors in lung cancers with a high-grade fetal adenocarcinoma component.

Background: High-grade fetal adenocarcinoma of the lung (H-FLAC) is a rare variant of pulmonary adenocarcinoma. Our previous study showed a high frequency of KMT2C mutations in lung cancers with an H-FLAC component, showing that KMT2C dysfunction may be associated with the biological features of H-FLACs. Methods: In this study, we performed RNA sequencing and immunohistochemical analysis to identify the differentially expressed genes and corresponding pathways associated with H-FLACs, compared with common adenocarcinomas. Results: Ingenuity pathway analysis based on RNA sequencing data revealed that DNA homologous recombination repair (HRR) pathways were significantly inactivated in H-FLAC. Expression of KMT2C, ATM, ATR, and BRCA2 was significantly lower in H-FLACs than in common adenocarcinomas, and BRCA1 expression showed a decreasing trend. Pearson correlation analyses for all cases revealed that KMT2C expression showed a strong positive correlation (R>0.7) with the expression of ATR, BRCA1, and BRCA2 genes and a moderately positive correlation with ATM expression (R=0.47). Immunohistochemical analysis showed significantly lower levels of KMT2C, ATM, ATR, and BRCA2 expression in H-FLACs than in common adenocarcinomas, and a trend of lower BRCA1 levels. Additionally, KMT2C expression showed a weak to moderate correlation with that of ATM, ATR, BRCA1, and BRCA2. Conclusions: Cancers containing H-FLAC components showed lower levels of KMT2C and HRR factors than common lung adenocarcinomas, and their levels exhibited a positive correlation. These results support the hypothesis that loss of KMT2C function decreases the expression of the HRR factors in H-FLACs. H-FLACs with low KMT2C expression may be a good indication for poly (ADP-ribose) polymerase (PARP) inhibitor-based therapy.

Single-cell sequencing on CD8+ TILs revealed the nature of exhausted T cells recognizing neoantigen and cancer/testis antigen in non-small cell lung cancer.

BACKGROUND: CD8+tumor infiltrating lymphocytes (TILs) are often observed in non-small cell lung cancers (NSCLC). However, the characteristics of CD8+ TILs, especially T-cell populations specific for tumor antigens, remain poorly understood. METHODS: High throughput single-cell RNA sequencing and single-cell T-cell receptor (TCR) sequencing were performed on CD8+ TILs from three surgically-resected lung cancer specimens. Dimensional reduction for clustering was performed using Uniform Manifold Approximation and Projection. CD8+ TIL TCR specific for the cancer/testis antigen KK-LC-1 and for predicted neoantigens were investigated. Differentially-expressed gene analysis, Gene Set Enrichment Analysis (GSEA) and single sample GSEA was performed to characterize antigen-specific T cells. RESULTS: A total of 6998 CD8+ T cells was analyzed, divided into 10 clusters according to their gene expression profile. An exhausted T-cell (exhausted T (Tex)) cluster characterized by the expression of ENTPD1 (CD39), TOX, PDCD1 (PD1), HAVCR2 (TIM3) and other genes, and by T-cell oligoclonality, was identified. The Tex TCR repertoire (Tex-TCRs) contained nine different TCR clonotypes recognizing five tumor antigens including a KK-LC-1 antigen and four neoantigens. By re-clustering the tumor antigen-specific T cells (n=140), it could be seen that the individual T-cell clonotypes were present on cells at different stages of differentiation and functional states even within the same Tex cluster. Stimulating these T cells with predicted cognate peptide indicated that TCR signal strength and subsequent T-cell proliferation and cytokine production was variable but always higher for neoantigens than KK-LC-1. CONCLUSIONS: Our approach focusing on T cells with an exhausted phenotype among CD8+ TILs may facilitate the identification of tumor antigens and clarify the nature of the antigen-specific T cells to specify the promising immunotherapeutic targets in patients with NSCLC.

Genetic analysis of low-grade adenosquamous carcinoma of the breast progressing to high-grade metaplastic carcinoma.

PURPOSE: Low-grade adenosquamous carcinoma (LGASC) is a rare type of metaplastic carcinoma of the breast (MBC) with an indolent clinical course. A few LGASC cases with high-grade transformation have been reported; however, the genetics underlying malignant progression of LGASC remain unclear. METHODS: We performed whole-genome sequencing analysis on five MBCs from four patients, including one case with matching primary LGASC and a lymph node metastatic tumor consisting of high-grade MBC with a predominant metaplastic squamous cell carcinoma component (MSC) that progressed from LGASC and three cases of independent de novo MSC. RESULTS: Unlike de novo MSC, LGASC and its associated MSC showed no TP53 mutation and tended to contain fewer structural variants than de novo MSC. Both LGASC and its associated MSC harbored the common GNAS c.C2530T:p.Arg844Cys mutation, which was more frequently detected in the cancer cell fraction of MSC. MSC associated with LGASC showed additional pathogenic deletions of multiple tumor-suppressor genes, such as KMT2D and BTG1. Copy number analysis revealed potential 18q loss of heterozygosity in both LGASC and associated MSC. The frequency of SMAD4::DCC fusion due to deletions increased with progression to MSC; however, chimeric proteins were not detected. SMAD4 protein expression was already decreased at the LGASC stage due to unknown mechanisms. CONCLUSION: Not only LGASC but also its associated high-grade MBC may be genetically different from de novo high-grade MBC. Progression from LGASC to high-grade MBC may involve the concentration of driver mutations caused by clonal selection and inactivation of tumor-suppressor genes.

Scribble mis-localization induces adaptive resistance to KRAS G12C inhibitors through feedback activation of MAPK signaling mediated by YAP-induced MRAS.

Tumor cells evade targeted drugs by rewiring their genetic and epigenetic networks. Here, we identified that inhibition of MAPK signaling rapidly induces an epithelial-to-mesenchymal transition program by promoting re-localization of an apical-basal polarity protein, Scribble, in oncogene-addicted lung cancer models. Mis-localization of Scribble suppressed Hippo-YAP signaling, leading to YAP nuclear translocation. Furthermore, we discovered that a RAS superfamily protein MRAS is a direct target of YAP. Treatment with KRAS G12C inhibitors induced MRAS expression, which formed a complex with SHOC2, precipitating feedback activation of MAPK signaling. Abrogation of YAP activation or MRAS induction enhanced the efficacy of KRAS G12C inhibitor treatment in vivo. These results highlight a role for protein localization in the induction of a non-genetic mechanism of resistance to targeted therapies in lung cancer. Furthermore, we demonstrate that induced MRAS expression is a key mechanism of adaptive resistance following KRAS G12C inhibitor treatment.

Bromodomain protein BRD8 regulates cell cycle progression in colorectal cancer cells through a TIP60-independent regulation of the pre-RC complex.

Bromodomain-containing protein 8 (BRD8) is a subunit of the NuA4/TIP60-histone acetyltransferase complex. Although BRD8 has been considered to act as a co-activator of the complex, its biological role remains to be elucidated. Here, we uncovered that BRD8 accumulates in colorectal cancer cells through the inhibition of ubiquitin-dependent protein degradation by the interaction with MRG domain binding protein. Transcriptome analysis coupled with genome-wide mapping of BRD8-binding sites disclosed that BRD8 transactivates a set of genes independently of TIP60, and that BRD8 regulates the expression of multiple subunits of the pre-replicative complex in concert with the activator protein-1. Depletion of BRD8 induced cell-cycle arrest at the G1 phase and suppressed cell proliferation. We have also shown that the bromodomain of BRD8 is indispensable for not only the interaction with histone H4 or transcriptional regulation but also its own protein stability. These findings highlight the importance of bromodomain as a therapeutic target.

Histological markers, sickle-shaped blood vessels, myxoid area, and infiltrating growth pattern help stratify the prognosis of patients with myxofibrosarcoma/undifferentiated sarcoma.

Myxofibrosarcoma (MFS) and undifferentiated sarcoma (US) have been considered as tumors of the same lineage based on genetic/epigenetic profiling. Although MFS shows a notably better prognosis than US, there are no clear criteria for distinguishing between them. Here, we examined 85 patients with MFS/US and found that tumors with infiltrative growth patterns tended to have more myxoid areas and higher local recurrence rates but fewer distant metastases and better overall survival. Morphologically characteristic sickle-shaped blood vessels, which tended to have fewer αSMA-positive cells, were also observed in these tumors, compared with normal vessels. Based on the incidence of these sickle-shaped blood vessels, we subdivided conventionally diagnosed US into two groups. This stratification was significantly correlated with metastasis and prognosis. RNA sequencing of 24 tumors (9 MFS and 15 US tumors) demonstrated that the proteasome, NF-kB, and VEGF pathways were differentially regulated among these tumors. Expression levels of KDR and NFATC4, which encode a transcription factor responsible for the neuritin-insulin receptor angiogenic signaling, were elevated in the sickle-shaped blood vessel-rich US tumors. These findings indicate that further analyses may help elucidate the malignant potential of MFS/US tumors as well as the development of therapeutic strategies for such tumors.

Artificial intelligence using deep learning analysis of endoscopic ultrasonography images for the differential diagnosis of pancreatic masses.

BACKGROUND : There are several types of pancreatic mass, so it is important to distinguish between them before treatment. Artificial intelligence (AI) is a mathematical technique that automates learning and recognition of data patterns. This study aimed to investigate the efficacy of our AI model using endoscopic ultrasonography (EUS) images of multiple types of pancreatic mass (pancreatic ductal adenocarcinoma [PDAC], pancreatic adenosquamous carcinoma [PASC], acinar cell carcinoma [ACC], metastatic pancreatic tumor [MPT], neuroendocrine carcinoma [NEC], neuroendocrine tumor [NET], solid pseudopapillary neoplasm [SPN], chronic pancreatitis, and autoimmune pancreatitis [AIP]). METHODS : Patients who underwent EUS were included in this retrospective study. The included patients were divided into training, validation, and test cohorts. Using these cohorts, an AI model that can distinguish pancreatic carcinomas from noncarcinomatous pancreatic lesions was developed using a deep-learning architecture and the diagnostic performance of the AI model was evaluated. RESULTS : 22 000 images were generated from 933 patients. The area under the curve, sensitivity, specificity, and accuracy (95 %CI) of the AI model for the diagnosis of pancreatic carcinomas in the test cohort were 0.90 (0.84-0.97), 0.94 (0.88-0.98), 0.82 (0.68-0.92), and 0.91 (0.85-0.95), respectively. The per-category sensitivities (95 %CI) of each disease were PDAC 0.96 (0.90-0.99), PASC 1.00 (0.05-1.00), ACC 1.00 (0.22-1.00), MPT 0.33 (0.01-0.91), NEC 1.00 (0.22-1.00), NET 0.93 (0.66-1.00), SPN 1.00 (0.22-1.00), chronic pancreatitis 0.78 (0.52-0.94), and AIP 0.73 (0.39-0.94). CONCLUSIONS : Our developed AI model can distinguish pancreatic carcinomas from noncarcinomatous pancreatic lesions, but external validation is needed.

Depletion of R270C Mutant p53 in Osteosarcoma Attenuates Cell Growth but Does Not Prevent Invasion and Metastasis In Vivo.

Novel therapeutic targets are needed to better treat osteosarcoma, which is the most common bone malignancy. We previously developed mouse osteosarcoma cells, designated AX (accelerated bone formation) cells from bone marrow stromal cells. AX cells harbor both wild-type and mutant forms of p53 (R270C in the DNA-binding domain, which is equivalent to human R273C). In this study, we showed that mutant p53 did not suppress the transcriptional activation function of wild-type p53 in AX cells. Notably, AXT cells, which are cells derived from tumors originating from AX cells, lost wild-type p53 expression, were devoid of the intact transcription activation function, and were resistant to doxorubicin. ChIP-seq analyses revealed that this mutant form of p53 bound to chromatin in the vicinity of the transcription start sites of various genes but exhibited a different binding profile from wild-type p53. The knockout of mutant p53 in AX and AXT cells by CRISPR-Cas9 attenuated tumor growth but did not affect the invasion of these cells. In addition, depletion of mutant p53 did not prevent metastasis in vivo. Therefore, the therapeutic potency targeting R270C (equivalent to human R273C) mutant p53 is limited in osteosarcoma. However, considering the heterogeneous nature of osteosarcoma, it is important to further evaluate the biological and clinical significance of mutant p53 in various cases.

Case report: Common clonal origin of concurrent langerhans cell histiocytosis and acute myeloid leukemia.

Langerhans cell histiocytosis (LCH) and acute myeloid leukemia (AML) are distinct entities of blood neoplasms, and the exact developmental origin of both neoplasms are considered be heterogenous among patients. However, reports of concurrent LCH and AML are rare. Herein we report a novel case of concurrent LCH and AML which shared same the driver mutations, strongly suggesting a common clonal origin.An 84-year-old female presented with cervical lymphadenopathy and pruritic skin rash on the face and scalp. Laboratory tests revealed pancytopenia with 13% of blasts, elevated LDH and liver enzymes, in addition to generalised lymphadenopathy and splenomegaly by computed tomography. Bone marrow specimens showed massive infiltration of MPO-positive myeloblasts, whereas S-100 and CD1a positive atypical dendritic cell-like cells accounted for 10% of the atypical cells on bone marrow pathology, suggesting a mixture of LCH and AML. A biopsy specimen from a cervical lymph node and the skin demonstrated the accumulation of atypical cells which were positive for S-100 and CD1a. LCH was found in lymph nodes, skin and bone marrow; AML was found in peripheral blood and bone marrow (AML was predominant compared with LCH in the bone marrow). Next generation sequencing revealed four somatic driver mutations (NRAS-G13D, IDH2-R140Q, and DNMT3A-F640fs/-I715fs), equally shared by both the lymph node and bone marrow, suggesting a common clonal origin for the concurrent LCH and AML. Prednisolone and vinblastine were initially given with partial response in LCH; peripheral blood blasts also disappeared for 3 months. Salvage chemotherapy with low dose cytarabine and aclarubicin were given for relapse, with partial response in both LCH and AML. She died from pneumonia and septicemia on day 384. Our case demonstrates a common cell of origin for LCH and AML with a common genetic mutation, providing evidence to support the proposal to classify histiocytosis, including LCH, as a myeloid/myeloproliferative malignancy.

The cAMP/PKA/CREB and TGFß/SMAD4 Pathways Regulate Stemness and Metastatic Potential in Colorectal Cancer Cells.

SIGNIFICANCE: This study identifies signaling pathways essential for maintaining the stemness and metastatic potential of colorectal cancer cells and proposes CREB as a therapeutic target in metastatic colorectal cancer.

Identification of bacteriophage genome sequences with representation learning.

MOTIVATION: Bacteriophages/phages are the viruses that infect and replicate within bacteria and archaea, and rich in human body. To investigate the relationship between phages and microbial communities, the identification of phages from metagenome sequences is the first step. Currently, there are two main methods for identifying phages: database-based (alignment-based) methods and alignment-free methods. Database-based methods typically use a large number of sequences as references; alignment-free methods usually learn the features of the sequences with machine learning and deep learning models. RESULTS: We propose INHERIT which uses a deep representation learning model to integrate both database-based and alignment-free methods, combining the strengths of both. Pre-training is used as an alternative way of acquiring knowledge representations from existing databases, while the BERT-style deep learning framework retains the advantage of alignment-free methods. We compare INHERIT with four existing methods on a third-party benchmark dataset. Our experiments show that INHERIT achieves a better performance with the F1-score of 0.9932. In addition, we find that pre-training two species separately helps the non-alignment deep learning model make more accurate predictions. AVAILABILITY AND IMPLEMENTATION: The codes of INHERIT are now available in: https://github.com/Celestial-Bai/INHERIT. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Xprediction: Explainable EGFR-TKIs response prediction based on drug sensitivity specific gene networks.

In recent years, drug sensitivity prediction has garnered a great deal of attention due to the growing interest in precision medicine. Several computational methods have been developed for drug sensitivity prediction and the identification of related markers. However, most previous studies have ignored genetic interaction, although complex diseases (e.g., cancer) involve many genes intricately connected in a molecular network rather than the abnormality of a single gene. To effectively predict drug sensitivity and understand its mechanism, we propose a novel strategy for explainable drug sensitivity prediction based on sample-specific gene regulatory networks, designated Xprediction. Our strategy first estimates sample-specific gene regulatory networks that enable us to identify the molecular interplay underlying varying clinical characteristics of cell lines. We then, predict drug sensitivity based on the estimated sample-specific gene regulatory networks. The predictive models are based on machine learning approaches, i.e., random forest, kernel support vector machine, and deep neural network. Although the machine learning models provide remarkable results for prediction and classification, we cannot understand how the models reach their decisions. In other words, the methods suffer from the black box problem and thus, we cannot identify crucial molecular interactions that involve drug sensitivity-related mechanisms. To address this issue, we propose a method that describes the importance of each molecular interaction for the drug sensitivity prediction result. The proposed method enables us to identify crucial gene-gene interactions and thereby, interpret the prediction results based on the identified markers. To evaluate our strategy, we applied Xprediction to EGFR-TKIs prediction based on drug sensitivity specific gene regulatory networks and identified important molecular interactions for EGFR-TKIs prediction. Our strategy effectively performed drug sensitivity prediction compared with prediction based on the expression levels of genes. We also verified through literature, the EGFR-TKIs-related mechanisms of a majority of the identified markers. We expect our strategy to be a useful tool for predicting tasks and uncovering complex mechanisms related to pharmacological profiles, such as mechanisms of acquired drug resistance or sensitivity of cancer cells.

Impact of salivary and pancreatic amylase gene copy numbers on diabetes, obesity, and functional profiles of microbiome in Northern Japanese population.

Amylase genes reside in a structurally complex locus, and their copy numbers vary greatly, and several studies have reported their association with obesity. The mechanism of this effect was partially explained by changes in the oral and gut microbiome compositions; however, a detailed mechanism has been unclarified. In this study, we showed their association with diabetes in addition to obesity, and further discovered a plausible mechanism of this association based on the function of commensal bacteria. First, we confirmed that the amylase copy number in the population tends to be larger than that reported in other studies and that there is a positive association between obesity and diabetes (p = 1.89E-2 and 8.63E-3). Second, we identified that relative abundance of some genus level microbiome, Capnocytophaga, Dialister, and previously reported bacteria, were significantly associated with amylase copy numbers. Finally, through functional gene-set analysis using shotgun sequencing, we observed that the abundance of genes in the Acarbose pathway in the gut microbiome was significantly decreased with an increase in the amylase copy number (p-value = 5.80E-4). Our findings can partly explain the mechanism underlying obesity and diabetes in populations with high amylase copy numbers.

New evaluation of the tumor immune microenvironment of non-small cell lung cancer and its association with prognosis.

BACKGROUND: A better understanding of the tumor immune microenvironment (TIME) will facilitate the development of prognostic biomarkers and more effective therapeutic strategies in patients with lung cancer. However, little has been reported on the comprehensive evaluation of complex interactions among cancer cells, immune cells, and local immunosuppressive elements in the TIME. METHODS: Whole-exome sequencing and RNA sequencing were carried out on 113 lung cancers. We performed single sample gene set enrichment analysis on TIME-related gene sets to develop a new scoring system (TIME score), consisting of T-score (tumor proliferation), I-score (antitumor immunity) and S-score (immunosuppression). Lung cancers were classified according to a combination of high or low T-score, I-score, and S-scores (eight groups; G1-8). Clinical and genomic features, and immune landscape were investigated among eight groups. The external data sets of 990 lung cancers from The Cancer Genome Atlas and 76 melanomas treated with immune checkpoint inhibitors (ICI) were utilized to evaluate TIME scoring and explore prognostic and predictive accuracy. RESULTS: The representative histological type including adenocarcinoma and squamous cell carcinoma, and driver mutations such as epidermal growth factor receptor and TP53 mutations were different according to the T-score. The numbers of somatic mutations and predicted neoantigens were higher in Thi (G5-8) than Tlo (G1-4) tumors. Immune selection pressure against neoantigen expression occurred only in Thi and was dampened in Thi/Ilo (G5-6), possibly due to a reduced number of T cells with a high proportion of tumor specific but exhausted cells. Thi/Ilo/Shi (G5) displayed the lowest immune responses by additional immune suppressive mechanisms. The T-score, I-score and S-scores were independent prognostic factors, with survival curves well separated into eight groups with G5 displaying the worst overall survival, while the opposite group Tlo/Ihi/Slo (G4) had the best prognosis. Several oncogenic signaling pathways influenced on T-score and I-scores but not S-score, and PI3K pathway alteration correlated with poor prognosis in accordance with higher T-score and lower I-score. Moreover, the TIME score predicted the efficacy of ICI in patients with melanoma. CONCLUSION: The TIME score capturing complex interactions among tumor proliferation, antitumor immunity and immunosuppression could be useful for prognostic predictions or selection of treatment strategies in patients with lung cancer.

Repeated Lineage Switches in an Elderly Case of Refractory B-Cell Acute Lymphoblastic Leukemia With MLL Gene Amplification: A Case Report and Literature Review.

Lineage switches in acute leukemia occur rarely, and the underlying mechanisms are poorly understood. Herein, we report the case of an elderly patient with leukemia in which the leukemia started as B-cell acute lymphoblastic leukemia (B-ALL) and later changed to B- and T-cell mixed phenotype acute leukemia (MPAL) and acute myeloid leukemia (AML) during consecutive induction chemotherapy treatments. A 65-year-old woman was initially diagnosed with Philadelphia chromosome-negative B-ALL primarily expressing TdT/CD34/HLA-DR; more than 20% of the blasts were positive for CD19/CD20/cytoplasmic CD79a/cytoplasmic CD22/CD13/CD71.The blasts were negative for T-lineage markers and myeloperoxidase (MPO). Induction chemotherapy with the standard regimen for B-ALL resulted in primary induction failure. After the second induction chemotherapy regimen, the blasts were found to be B/T bi-phenotypic with additional expression of cytoplasmic CD3. A single course of clofarabine (the fourth induction chemotherapy regimen) dramatically reduced lymphoid marker levels. However, the myeloid markers (e.g., MPO) eventually showed positivity and the leukemia completely changed its lineage to AML. Despite subsequent intensive chemotherapy regimens designed for AML, the patient's leukemia was uncontrollable and a new monoblastic population emerged. The patient died approximately 8 months after the initial diagnosis without experiencing stable remission. Several cytogenetic and genetic features were commonly identified in the initial diagnostic B-ALL and in the following AML, suggesting that this case should be classified as lineage switching leukemia rather than multiple simultaneous cancers (i.e., de novo B-ALL and de novo AML, or primary B-ALL and therapy-related myeloid neoplasm). A complex karyotype was persistently observed with a hemi-allelic loss of chromosome 17 (the location of the TP53 tumor suppressor gene). As the leukemia progressed, the karyotype became more complex, with the additional abnormalities. Sequential target sequencing revealed an increased variant allele frequency of TP53 mutation. Fluorescent in situ hybridization (FISH) revealed an increased number of mixed-lineage leukemia (MLL) genes, both before and after lineage conversion. In contrast, FISH revealed negativity for MLL rearrangements, which are well-known abnormalities associated with lineage switching leukemia and MPAL. To our best knowledge, this is the first reported case of acute leukemia presenting with lineage ambiguity and MLL gene amplification.

Perioperative circulating tumor DNA enables the identification of patients with poor prognosis in upper tract urothelial carcinoma.

Perioperative systemic chemotherapy improves the prognosis of upper tract urothelial carcinoma (UTUC). The first objective of this study was to verify whether perioperative circulating tumor DNA (ctDNA) analysis using a pan-cancer gene panel and next-generation sequencing could identify patients with poor prognosis who require perioperative chemotherapy. Second, we investigated whether ctDNA is useful for minimal residual disease (MRD) detection and treatment monitoring in UTUC. This study included 50 patients with untreated UTUC, including 43 cases of localized UTUC. We performed targeted ultradeep sequencing of plasma cell-free DNA (cfDNA) and buffy coat DNA and whole-exome sequencing of cancer tissues, allowing exclusion of possible false positives. We attempted to stratify the prognosis according to the perioperative ctDNA levels in patients with localized UTUC. In patients with metastatic UTUC, ctDNA was evaluated before, during, and after systemic treatment. In total, 23 (46%) of 50 patients with untreated UTUC were ctDNA positive, and 17 (40%) of 43 patients with localized UTUC were ctDNA positive. Of the detected TP53 mutations, 19% were false positives due to clonal hematopoiesis of indeterminate potential. Among preoperative risk factors, only the preoperative ctDNA fraction>2% was a significant and independent risk factor associated with worse recurrence-free survival (RFS). Furthermore, the existence of ctDNA early points after the operation was significantly associated with worse RFS, suggesting the presence of MRD. ctDNA also showed a potential as a real-time marker for systemic therapy in patients with metastatic UTUC. Detection of ctDNA may indicate potential metastasis and guide decisions on perioperative chemotherapy.

Early dynamics of circulating tumor DNA predict clinical response to immune checkpoint inhibitors in metastatic renal cell carcinoma.

OBJECTIVES: Detection of genomic alterations in circulating tumor deoxyribonucleic acid of peripheral blood can guide the selection of systemic therapy in cancer patients. The predictive significance of circulating tumor deoxyribonucleic acid in metastatic renal cell carcinoma remains unclear, especially for patients treated with immune checkpoint inhibitors. METHODS: In this study, we collected plasma samples before and 1 month after commencing nivolumab monotherapy or nivolumab plus ipilimumab therapy from 14 metastatic renal cell carcinoma patients. We performed circulating tumor deoxyribonucleic acid genomic profiling in plasma cell-free deoxyribonucleic acid by next-generation sequencing using a commercially available pan-cancer panel (Guardant360 CDx). Additionally, we also performed whole exome sequencing of tumor tissues and compared the concordance of genomic profiles with circulating tumor deoxyribonucleic acid. RESULTS: Nine patients had circulating tumor deoxyribonucleic acid in pretreatment plasma samples with a total of 20 mutations (15 single nucleotide variants, three insertions/deletions, and two copy number amplification). VHL (30.0%) was the most frequently mutated gene, followed by TP53 (20.0%), and 45.0% of circulating tumor deoxyribonucleic acid mutations were concordant with somatic mutations in tumor tissues. Patients with decreasing circulating tumor deoxyribonucleic acid mutant allele frequency had better progression free survival when compared to those with increasing mutant allele frequency (P = 0.0441). CONCLUSIONS: Our findings revealed that early circulating tumor deoxyribonucleic acid dynamics can serve as a predictive biomarker for response to immune checkpoint inhibitors in metastatic renal cell carcinoma patients.

MEK/ERK-mediated oncogenic signals promote secretion of extracellular vesicles by controlling lysosome function.

Cancer cells secrete large amounts of extracellular vesicles (EVs) originating from multivesicular bodies (MVBs). Mature MVBs fuse either with the plasma membrane for release as EVs, often referred as to exosomes or with lysosomes for degradation. However, the mechanisms regulating MVB fate remain unknown. Here, we investigated the regulators of MVB fate by analyzing the effects of signaling inhibitors on EV secretion from cancer cells engineered to secrete luciferase-labeled EVs. Inhibition of the oncogenic MEK/ERK pathway suppressed EV release and activated lysosome formation. MEK/ERK-mediated lysosomal inactivation impaired MVB degradation, resulting in increased EV secretion from cancer cells. Moreover, MEK/ERK inhibition prevented c-MYC expression and induced the nuclear translocation of MiT/TFE transcription factors, thereby promoting the activation of lysosome-related genes, including the gene encoding a subunit of vacuolar-type H+ -ATPase, which is responsible for lysosomal acidification and function. Furthermore, c-MYC upregulation was associated with lysosomal gene downregulation in MEK/ERK-activated renal cancer cells/tissues. These findings suggest that the MEK/ERK/c-MYC pathway controls MVB fate and promotes EV production in human cancers by inactivating lysosomal function.

IL-23 production in human macrophages is regulated negatively by tumor necrosis factor α-induced protein 3 and positively by specificity protein 1 after stimulation of the toll-like receptor 7/8 signaling pathway.

The IL-23/IL-17 axis plays an important role in the development of autoimmune diseases, but the mechanism regulating IL-23 production is mainly unknown. We investigated how TNFAIP3 and Sp1 affect IL-23 production by human macrophages after exposure to resiquimod, a TLR7/8 agonist. IL-23 production was significantly upregulated by resiquimod but only slightly by LPS (a TLR4 agonist). Interestingly, IL-23 levels were significantly attenuated after sequential stimulation with LPS and resiquimod, but IL-12p40 and IL-18 levels were not. TLR4-related factors induced by LPS may regulate IL-23 expression via TLR7/8 signaling. LPS significantly enhanced TNFAIP3 and IRAK-M levels but reduced Sp1 levels. After exposure to resiquimod, RNA interference of TNFAIP3 upregulated IL-23 significantly more than siRNA transfection of IRAK-M did. In contrast, knockdown of Sp1 by RNA interference significantly attenuated IL-23 production. Transfection with siRNA for TNFAIP3 enhanced IL-23 expression significantly. After stimulation with resiquimod, GW7647-an agonist for PPARα (an inducer of NADHP oxidase)-and siRNA for UCP2 (a negative regulator of mitochondrial ROS generation) enhanced TNFAIP3 and reduced IL-23. siRNA for p22phox and gp91phox slightly increased Sp1 levels. However, after exposure to resiquimod siRNA-mediated knockout of DUOX1/2 significantly enhanced Sp1 and IL-23 levels, and decreased TNFα-dependent COX-2 expression. Concomitantly, TNFAIP3 levels was attenuated by DUOX1/2 siRNA. TNFAIP3 and Sp1 levels are reciprocally regulated through ROS generation. In conclusion, after stimulation of the TLR7/8 signaling pathway IL-23 production in human macrophages is regulated negatively by TNFAIP3.