RPS24 alternative splicing is a marker of cancer progression and epithelial-mesenchymal transition.

Although alternative splicing (AS) is a major mechanism that adds diversity to gene expression patterns, its precise role in generating variability in ribosomal proteins, known as ribosomal heterogeneity, remains unclear. The ribosomal protein S24 (RPS24) gene, encoding a ribosomal component, undergoes AS; however, in-depth studies have been challenging because of three microexons between exons 4 and 6. We conducted a detailed analysis of RPS24 AS isoforms using a direct approach to investigate the splicing junctions related to these microexons, focusing on four AS isoforms. Each of these isoforms showed tissue specificity and relative differences in expression among cancer types. Significant differences in the proportions of these RPS24 AS isoforms between cancerous and normal tissues across diverse cancer types were also observed. Our study highlighted a significant correlation between the expression levels of a specific RPS24 AS isoform and the epithelial-mesenchymal transition process in lung and breast cancers. Our research contributes to a better understanding of the intricate regulatory mechanisms governing AS of ribosomal protein genes and highlights the biological implications of RPS24 AS isoforms in tissue development and tumorigenesis.

GenoMycAnalyzer: a web-based tool for species and drug resistance prediction for Mycobacterium genomes.

BACKGROUND: Drug-resistant tuberculosis (TB) is a major threat to global public health. Whole-genome sequencing (WGS) is a useful tool for species identification and drug resistance prediction, and many clinical laboratories are transitioning to WGS as a routine diagnostic tool. However, user-friendly and high-confidence automated bioinformatics tools are needed to rapidly identify M. tuberculosis complex (MTBC) and non-tuberculous mycobacteria (NTM), detect drug resistance, and further guide treatment options. RESULTS: We developed GenoMycAnalyzer, a web-based software that integrates functions for identifying MTBC and NTM species, lineage and spoligotype prediction, variant calling, annotation, drug-resistance determination, and data visualization. The accuracy of GenoMycAnalyzer for genotypic drug susceptibility testing (gDST) was evaluated using 5,473 MTBC isolates that underwent phenotypic DST (pDST). The GenoMycAnalyzer database was built to predict the gDST for 15 antituberculosis drugs using the World Health Organization mutational catalogue. Compared to pDST, the sensitivity of drug susceptibilities by the GenoMycAnalyzer for first-line drugs ranged from 95.9% for rifampicin (95% CI 94.8-96.7%) to 79.6% for pyrazinamide (95% CI 76.9-82.2%), whereas those for second-line drugs ranged from 98.2% for levofloxacin (95% CI 90.1-100.0%) to 74.9% for capreomycin (95% CI 69.3-80.0%). Notably, the integration of large deletions of the four resistance-conferring genes increased gDST sensitivity. The specificity of drug susceptibilities by the GenoMycAnalyzer ranged from 98.7% for amikacin (95% CI 97.8-99.3%) to 79.5% for ethionamide (95% CI 76.4-82.3%). The incorporated Kraken2 software identified 1,284 mycobacterial species with an accuracy of 98.8%. GenoMycAnalyzer also perfectly predicted lineages for 1,935 MTBC and spoligotypes for 54 MTBC. CONCLUSIONS: GenoMycAnalyzer offers both web-based and graphical user interfaces, which can help biologists with limited access to high-performance computing systems or limited bioinformatics skills. By streamlining the interpretation of WGS data, the GenoMycAnalyzer has the potential to significantly impact TB management and contribute to global efforts to combat this infectious disease. GenoMycAnalyzer is available at http://www.mycochase.org .

Integrated Bioinformatics Analysis Identified ASNS and DDIT3 as the Therapeutic Target in Castrate-Resistant Prostate Cancer.

Many studies have demonstrated the mechanisms of progression to castration-resistant prostate cancer (CRPC) and novel strategies for its treatment. Despite these advances, the molecular mechanisms underlying the progression to CRPC remain unclear, and currently, no effective treatments for CRPC are available. Here, we characterized the key genes involved in CRPC progression to gain insight into potential therapeutic targets. Bicalutamide-resistant prostate cancer cells derived from LNCaP were generated and named Bical R. RNA sequencing was used to identify differentially expressed genes (DEGs) between LNCaP and Bical R. In total, 631 DEGs (302 upregulated genes and 329 downregulated genes) were identified. The Cytohubba plug-in in Cytoscape was used to identify seven hub genes (ASNS, AGT, ATF3, ATF4, DDIT3, EFNA5, and VEGFA) associated with CRPC progression. Among these hub genes, ASNS and DDIT3 were markedly upregulated in CRPC cell lines and CRPC patient samples. The patients with high expression of ASNS and DDIT3 showed worse disease-free survival in patients with The Cancer Genome Atlas (TCGA)-prostate adenocarcinoma (PRAD) datasets. Our study revealed a potential association between ASNS and DDIT3 and the progression to CRPC. These results may contribute to the development of potential therapeutic targets and mechanisms underlying CRPC progression, aiming to improve clinical efficacy in CRPC treatment.

Intratumoral IL-12 delivery via mesenchymal stem cells combined with PD-1 blockade leads to long-term antitumor immunity in a mouse glioblastoma model.

BACKGROUND: Although PD-1 blockade is effective for treating several types of cancer, the efficacy of this agent in glioblastoma is largely limited. To overcome non-responders and the immunosuppressive tumor microenvironment, combinational immunotherapeutic strategies with anti-PD-1 need to be considered. Here, we developed IL-12-secreting mesenchymal stem cells (MSC_IL-12) with glioblastoma tropism and evaluated the therapeutic effects of anti-PD-1, MSC_IL-12, and their combination against glioblastoma. METHODS: Therapeutic responses were evaluated using an immunocompetent mouse orthotopic model. Tumor-infiltrating lymphocytes (TILs) were analyzed using immunofluorescent imaging. Single-cell transcriptome was obtained from mouse brains after treatments. RESULTS: Anti-PD-1 and MSC_IL-12 showed complete tumor remission in 25.0% (4/16) and 23.1% (3/13) of glioblastoma-implanted mice, respectively, and their combination yielded synergistic antitumor efficacy indicated by 50.0% (6/12) of complete tumor remission. Analyses of TILs revealed that anti-PD-1 increased CD8+ T cells, while MSC_IL-12 led to infiltration of CD4+ T cells and NK cells. Both therapies reduced frequencies of Tregs. All these aspects observed in each monotherapy group were superimposed in the combination group. Notably, no tumor growth was observed upon rechallenge in cured mice, indicating long-term immunity against glioblastoma provoked by the therapies. Single-cell RNA-seq data confirmed these results and revealed that the combined treatment led to immune-favorable tumor microenvironment-CD4+, CD8+ T cells, effector memory T cells, and activated microglia were increased, whereas exhausted T cells, Tregs, and M2 polarized microglia were reduced. CONCLUSION: Anti-PD-1 and MSC_IL-12 monotherapies show long-term therapeutic responses, and their combination further enhances antitumor efficacy against glioblastoma via inducing immune-favorable tumor microenvironment.

Establishment of tumor microenvironment-preserving organoid model from patients with intracranial meningioma.

BACKGROUND: Although meningioma is the most common primary brain tumor, treatments rely on surgery and radiotherapy, and recurrent meningiomas have no standard therapeutic options due to a lack of clinically relevant research models. Current meningioma cell lines or organoids cannot reflect biological features of patient tumors since they undergo transformation along culture and consist of only tumor cells without microenvironment. We aim to establish patient-derived meningioma organoids (MNOs) preserving diverse cell types representative of the tumor microenvironment. METHODS: The biological features of MNOs were evaluated using WST, LDH, and collagen-based 3D invasion assays. Cellular identities in MNOs were confirmed by immunohistochemistry (IHC). Genetic alteration profiles of MNOs and their corresponding parental tumors were obtained by whole-exome sequencing. RESULTS: MNOs were established from four patients with meningioma (two grade 1 and two grade 2) at a 100% succession rate. Exclusion of enzymatic dissociation-reaggregation steps endowed MNOs with original histology and tumor microenvironment. In addition, we used a liquid media culture system instead of embedding samples into Matrigel, resulting in an easy-to-handle, cost-efficient, and time-saving system. MNOs maintained their functionality and morphology after long-term culture (> 9 wk) and repeated cryopreserving-recovery cycles. The similarities between MNOs and their corresponding parental tumors were confirmed by both IHC and whole-exome sequencing. As a representative application, we utilized MNOs in drug screening, and mifepristone, an antagonist of progesterone receptor, showed prominent antitumor efficacy with respect to viability, invasiveness, and protein expression. CONCLUSION: Taken together, our MNO model overcame limitations of previous meningioma models and showed superior resemblance to parental tumors. Thus, our model could facilitate translational research identifying and selecting drugs for meningioma in the era of precision medicine.

Spatial architectures of somatic mutations in normal prostate, benign prostatic hyperplasia and coexisting prostate cancer.

This study aimed to identify somatic mutations in nontumor cells (NSMs) in normal prostate and benign prostatic hyperplasia (BPH) and to determine their relatedness to prostate cancer (PCA). From 22 PCA patients, two prostates were sampled for 3-dimensional mapping (50 normal, 46 BPH and 1 PCA samples), and 20 prostates were trio-sampled (two normal or BPH samples and one PCA sample) and analyzed by whole-genome sequencing. Normal and BPH tissues harbored several driver NSMs and copy number alterations (CNAs), including in FOXA1, but the variations exhibited low incidence, rare recurrence, and rare overlap with PCAs. CNAs, structural variants, and mutation signatures were similar between normal and BPH samples, while BPHs harbored a higher mutation burden, shorter telomere length, larger clone size, and more private NSMs than normal prostates. We identified peripheral-zonal dominance and right-side asymmetry in NSMs, but the asymmetry was heterogeneous between samples. In one normal prostate, private oncogenic RAS-signaling NSMs were detected, suggesting convergence in clonal maintenance. Early embryonic mutations exhibited two distinct distributions, characterized as layered and mixed patterns. Our study identified that the BPH genome differed from the normal prostate genome but was still closer to the normal genome than to the PCA genome, suggesting that BPH might be more related to aging or environmental stress than to tumorigenic processes.

Single-cell profiling identifies distinct hormonal, immunologic, and inflammatory signatures of endometriosis-constituting cells.

Endometriosis consists of ectopic endometrial epithelial cells (EEECs) and ectopic endometrial stromal cells (EESCs) mixed with heterogeneous stromal cells. To address how endometriosis-constituting cells are different from normal endometrium and among endometriosis subtypes and how their molecular signatures are related to phenotypic manifestations, we analyzed ovarian endometrial cyst (OEC), superficial peritoneal endometriosis (SPE), and deep infiltrating endometriosis (DIE) from 12 patients using single-cell RNA-sequencing (scRNA-seq). We identified 11 cell clusters, including EEEC, EESC, fibroblasts, inflammatory/immune, endothelial, mesothelial, and Schwann cells. For hormonal signatures, EESCs, but not EEECs, showed high estrogen signatures (estrogen response scores and HOXA downregulation) and low progesterone signatures (DKK1 downregulation) compared to normal endometrium. In EEECs, we found MUC5B+ TFF3low cells enriched in endometriosis. In lymphoid cells, evidence for both immune activation (high cytotoxicity in NK) and exhaustion (high checkpoint genes in NKT and cytotoxic T) was identified in endometriosis. Signatures and subpopulations of macrophages were remarkably different among endometriosis subtypes with increased monocyte-derived macrophages and IL1B expression in DIE. The scRNA-seq predicted NRG1 (macrophage)-ERBB3 (Schwann cell) interaction in endometriosis, expressions of which were validated by immunohistochemistry. Myofibroblast subpopulations differed according to the location (OECs from fibroblasts and SPE/DIEs from mesothelial cells and fibroblasts). Endometriosis endothelial cells displayed proinflammation, angiogenesis, and leaky permeability signatures that were enhanced in DIE. Collectively, our study revealed that (1) many cell types-endometrial, lymphoid, macrophage, fibroblast, and endothelial cells-are altered in endometriosis; (2) endometriosis cells show estrogen responsiveness, immunologic cytotoxicity and exhaustion, and proinflammation signatures that are different in endometriosis subtypes; and (3) novel endometriosis-specific findings of MUC5B+ EEECs, mesothelial cell-derived myofibroblasts, and NRG1-ERBB3 interaction may underlie the pathogenesis of endometriosis. Our results may help extend pathologic insights, dissect aggressive diseases, and discover therapeutic targets in endometriosis. © 2023 The Pathological Society of Great Britain and Ireland.

Leprosy-specific subsets of macrophages and Schwann cells identified by single-cell RNA-sequencing.

In Mycobacterium leprae (M. leprae)-infection, inflammatory cells' subsets and dynamics as well as the interactions with Schwann cells have remained elusive. We investigated individual cells in M. leprae-inoculated nude mice by single-cell RNA-sequencing (scRNA-seq). For macrophages, we dissected two M1-like subsets and five M2-like subsets, where lipid-associated signatures were pervasive in both M1-like and M2-like subsets. There were four macrophage trajectories showing: (i) pro-inflammatory (M1), (ii) lipid metabolism-related (M2), (iii) anti-inflammatory (M2), and (iv) interferon-stimulated gene-related (M2) fates. They displayed early divergence without ever rejoining along the paths, suggesting simultaneous or continuous stimuli for macrophage activation in leprosy. The scRNA-seq predicted Schwann cell-macrophage interactions (Notch1-Jag1, Plxnb1-Sema4d interactions). An immature Schwann cell subset showing Tfap2a expression was identified, indicating Schwann cell dedifferentiation in leprosy tissues. Expressions of Notch1, Jag1, Plxnb1, Sema4d, and Tfap2a were validated in mouse or human leprosy tissues by immunohistochemistry. We identified both pro-inflammatory and inflammation-resolution signatures, where lipid-associated signatures were pervasive to the macrophages, representing leprosy-specific macrophage states for prolonged and repeated episodes of inflammation and resolution. Our study identified refined molecular states and interactions of macrophages and Schwann cells, suggesting novel insights into the pathogenesis of unhealed inflammation with neuropathy and potential therapeutic targets for leprosy.

Monitoring the Outcomes of Systemic Chemotherapy Including Immune Checkpoint Inhibitor for HER2-Positive Metastatic Gastric Cancer by Liquid Biopsy.

PURPOSE: For precision medicine, exploration and monitoring of molecular biomarkers are essential. However, in advanced gastric cancer (GC) with visceral lesions, an invasive procedure cannot be performed repeatedly for the follow-up of molecular biomarkers. MATERIALS AND METHODS: To verify the clinical implication of serial liquid biopsies targeting circulating tumor DNA (ctDNA) on treatment response, we conducted targeted deep sequencing for serially collected ctDNA of 15 HER2-positive metastatic GC patients treated with anti-PD-1 inhibitor in combination with standard systemic treatment. RESULTS: In the baseline ctDNAs, 14 patients (93%) harbored more than one genetic alteration. A number of mutations in well-known cancer-related genes, such as KRAS and PIK3CA, were identified. Copy number alterations were identified in eight GCs (53.3%), and amplification of the ERBB2 gene (6/15, 40.0%) was the most recurrent. When we calculated the mean variant allele frequency (VAF) of mutations in each ctDNA as the molecular tumor burden index (mTBI), the mTBI trend was largely consistent with the VAF profiles in both responder and non-responder groups. Notably, in the longitudinal analysis of ctDNA, mTBI provided 2-42 weeks (mean 13.4 weeks) lead time in the detection of disease progression compared to conventional follow-up with CT imaging. CONCLUSION: Our data indicate that the serial genetic alteration profiling of ctDNA is feasible to predict treatment response in HER2-positive GC patients in a minimally invasive manner. Practically, ctDNA profiles are useful not only for the molecular diagnosis of GC but also for the selection of GC patients with poor prognosis for systemic treatment (ClinicalTrials.gov identifier: NCT02901301).

Single-cell RNA sequencing of a poorly metastatic melanoma cell line and its subclones with high lung and brain metastasis potential reveals gene expression signature of metastasis with prognostic implication.

The molecular mechanisms underlying melanoma metastasis remain poorly understood. In this study, we aimed to delineate the mechanisms underlying gene expression alterations during metastatic potential acquisition and characterize the metastatic subclones within primary cell lines. We performed single-cell RNA sequencing of a poorly metastatic melanoma cell line (WM239A) and its subclones with high metastatic potential to the lung (113/6-4L) and the brain (131/4-5B1 and 131/4-5B2). Unsupervised clustering of 8173 melanoma cells identified three distinct clusters according to cell type ('Primary', 'Lung' and 'Brain' clusters) with differential expression of MITF and AXL pathways and putative cancer and cell cycle drivers, with the lung cluster expressing intermediate but distinct gene profiles between primary and brain clusters. Principal component (PC) analysis revealed that PC2 (the second PC), which was positively associated with MITF expression and negatively with AXL pathways, primarily segregated cell types, in addition to PC1 of the cell cycle pathway. Pseudotime trajectory and RNA velocity analyses suggested the existence of cellular subsets with metastatic potential in the Primary cluster and an association between PC2 signature alteration and metastasis potential acquisition. Analysis of The Cancer Genome Atlas melanoma samples by clustering into PC2-high and -low clusters by quartiles of PC2 signature expression revealed that the PC2-high cluster was an independent significant factor for poor prognosis (p-value = 0.003) with distinct genomic and transcriptomic characteristics, compared to the PC2-low cluster. In conclusion, we identified signatures of melanoma metastasis with prognostic significance and putative pro-metastatic subclones within a primary cell line.

Suppression of Metastatic Ovarian Cancer Cells by Bepridil, a Calcium Channel Blocker.

Although surgery followed by platinum-based therapy is effective as a standard treatment in the early stages of ovarian cancer, the majority of cases are diagnosed at advanced stages, leading to poor prognosis. Thus, the identification of novel therapeutic drugs is needed. In this study, we assessed the effectiveness of bepridil-a calcium channel blocker-in ovarian cancer cells using two cell lines: SKOV-3, and SKOV-3-13 (a highly metastatic clone of SKOV-3). Treatment of these cell lines with bepridil significantly reduced cell viability, migration, and invasion. Notably, SKOV-3-13 was more sensitive to bepridil than SKOV-3. The TGF-ß1-induced epithelial-mesenchymal transition (EMT)-like phenotype was reversed by treatment with bepridil in both cell lines. Consistently, expression levels of EMT-related markers, including vimentin, ß-catenin, and Snail, were also substantially decreased by the treatment with bepridil. An in vivo mouse xenograft model was used to confirm these findings. Tumor growth was significantly reduced by bepridil treatment in SKOV-3-13-inoculated mice, and immunohistochemistry showed consistently decreased expression of EMT-related markers. Our findings are the first to report anticancer effects of bepridil in ovarian cancer, and they suggest that bepridil holds significant promise as an effective therapeutic agent for targeting metastatic ovarian cancer.

Single-cell RNA sequencing reveals a pro-metastatic subpopulation and the driver transcription factor NFE2L1 in ovarian cancer cells.

BACKGROUND: Although cytoreductive surgery followed by adjuvant chemotherapy is effective as a standard treatment for early-stage ovarian cancer, the majority of ovarian cancer cases are diagnosed at the advanced stages with dissemination to the peritoneal cavity, leading to a poor prognosis. Therefore, it is crucial to understand the cellular and molecular mechanisms underlying metastasis and identify novel therapeutic targets. OBJECTIVE: In this study, we aimed to elucidate the mechanisms underlying gene expression alterations during the acquisition of metastatic potential and characterize the metastatic subpopulations within ovarian cancer cells. METHODS: We conducted single-cell RNA sequencing of two human ovarian cancer cell lines: SKOV-3 and SKOV-3-13, a highly metastatic subclone of SKOV-3. Suppression of NFE2L1 expression was performed through siRNA-mediated knockdown and CRISPR-Cas9-mediated knockout. RESULTS: Clustering and pseudotime trajectory analysis revealed pro-metastatic subpopulation within these cells. Furthermore, gene set enrichment analysis and prognosis analysis indicated that NFE2L1 could be a key transcription factor in the acquisition of metastasis potential. Inhibition of NFE2L1 significantly reduced migration and viability of both cells. In addition, NFE2L1 knockout cells exhibited significantly reduced tumor growth in a mouse xenograft model, recapitulating in silico and in vitro results. CONCLUSION: The results presented in this study deepen our understanding of the molecular pathogenesis of ovarian cancer metastasis with the ultimate goal of developing treatments targeting pro-metastatic subclones prior to metastasis.

Whole-exome sequencing of secondary tumors arising from nevus sebaceous revealed additional genomic alterations besides RAS mutations.

Nevus sebaceous (NS) is a congenital hamartoma associated with an increased risk of secondary neoplasms in approximately 10%-20% of patients. However, additional genomic alterations underlying tumorigenesis in NS lesions have not been clarified. We performed whole-exome sequencing of archived tumor tissues (n = 8; six basal cell carcinomas and two trichoepitheliomas) and matched germline tissues (n = 7) with from seven patients with secondary tumors arising from NS. We also analyzed NS lesions without secondary tumors (n = 8). Somatic mutations and copy number alterations (CNAs) were analyzed. We identified a median of 129 somatic mutations (corresponding to 2.6/Mb in target regions, range 26-336) for eight tumors, while a median of 118 somatic mutations (2.3/Mb, range 1-196) for eight NS lesions. Known RAS hotspot mutations were found in seven of the eight tumors (six for HRAS p.G13R and one for HRAS p.Q61R) and in six of the eight NS lesions (four for HRAS p.G13R, one for KRAS p.G12C, and one KRAS p.G12D). Except RAS mutations, several putative driver mutations were detected in tumors: TP53 p.F134L/p.R213*, MYCN p.P59L, OR2Z1 p.P167S, PTPN14 p.Q768*, and SMO p.W535L. As for CNAs, two tumors harbored copy-loss in regions encompassing PTCH1 gene. However, eight NS lesions did not harbor both putative driver mutations and CNAs. In conclusion, our study revealed that secondary tumors arising from NS harbor known RAS hotspot mutations and additional genomic alterations, including putative driver mutations and PTCH1 copy-loss. These results could help to define the high-risk group for tumor development in patients with NS and provide evidence for prophylactic resection.

Mutational Landscape of Normal Human Skin: Clues to Understanding Early-Stage Carcinogenesis in Keratinocyte Neoplasia.

Normal skin contains numerous clones carrying cancer driver mutations. However, the mutational landscape of normal skin and its clonal relationship with skin cancer requires further elucidation. The aim of our study was to investigate the mutational landscape of normal human skin. We performed whole-exome sequencing using physiologically normal skin tissues and the matched peripheral blood (n = 39) and adjacent-matched skin cancers from a subset of patients (n = 10). Exposed skin harbored a median of 530 mutations (10.4/mb, range = 51-2,947), whereas nonexposed skin majorly exhibited significantly fewer mutations (median = 13, 0.25/mb, range = 1-166). Patient age was significantly correlated with the mutational burden. Mutations in six driver genes (NOTCH1, FAT1, TP53, PPM1D, KMT2D, and ASXL1) were identified. De novo mutational signature analysis identified a single signature with components of UV- and aging-related signatures. Normal skin harbored only three instances of copy-neutral loss of heterozygosity in 9q (n = 2) and 6q (n = 1). The mutational burden of normal skin was not correlated with that of matched skin cancers, and no protein-coding mutations were shared. In conclusion, we revealed the mutational landscape of normal skin, highlighting the role of driver genes in the malignant progression of normal skin.

Alternative splicing: a new breakthrough for understanding tumorigenesis and potential clinical applications.

BACKGROUND: Alternative splicing (AS) is a post-transcriptional process that produces transcript variants, thus leading to transcriptome complexity. Recently, the scope of AS studies has been greatly expanded toward clinical applications owing to the abundance of RNA sequencing data. OBJECTIVE: This review consists of two parts. We first summarize bioinformatic resources that are useful for large-scale cancer-related AS studies. We then highlight the research efforts to utilize AS events for predicting clinical outcomes and planning therapeutic strategies. RESULTS: Computational approaches to interrogate AS events have been reviewed under three categories: (1) databases to provide functional and clinical annotation of AS events, (2) analytical tools to identify cancer-associated AS event, and (3) methods to identify splicing-related DNA variants and splicing-derived neoantigens. We also present the recent progress in exploring the clinical utility of AS under four categories: (1) identification of AS events for cancer prognosis, (2) utilization of AS events in molecular classification of various cancers, (3) regulatory mechanisms of AS underlying drug resistance, and (4) potential use of AS in cancer therapy. CONCLUSION: This review will be helpful for understanding the biological implications of AS in cancer and facilitate the development of AS markers for cancer prognosis and treatment. We anticipate that future studies will lead to the application of genome-wide AS profiles in cancer precision medicine.

Targeted deep sequencing reveals genomic alterations of actinic keratosis/cutaneous squamous cell carcinoma in situ and cutaneous squamous cell carcinoma.

Actinic keratosis (AK) and cutaneous squamous cell carcinoma in situ (CIS) are two of the most common precursors of cutaneous squamous cell carcinoma (cSCC). However, the genomic landscape of AK/CIS and the drivers of cSCC progression remain to be elucidated. The aim of our study was to investigate the genomic alterations between AK/CIS and cSCC in terms of somatic mutations and copy number alterations (CNAs). We performed targeted deep sequencing of 160 cancer-related genes with a median coverage of 515× for AK (N = 9), CIS (N = 9), cSCC lesions (N = 13), and matched germline controls from 17 patients. cSCC harboured higher abundance of total mutations, driver mutations and CNAs than AK/CIS. Driver mutations were found in TP53 (81%), NOTCH1 (32%), RB1 (26%) and CDKN2A (19%). All AK/CIS and cSCC lesions (93.5%), except two, harboured TP53 or NOTCH1 mutations, some of which were known oncogenic mutations or reported mutations in normal skin. RB1 driver mutations were found in CIS/cSCC (36.4%) but not in AK. CDKN2A driver mutations were found more frequently in cSCC (30.8%) than in AK/CIS (11.1%). Among recurrent (≥3 samples) CNAs (gain in MYC and PIK3CA/SOX2/TP63; loss in CDKN2A and RB1), MYC (8q) gain and CDKN2A (9p) loss were more frequently detected in cSCC (30.8%) than in AK/CIS (11.1%). Ultraviolet was responsible for the majority of somatic mutations in both AK/CIS and cSCC. Our study revealed that AK/CIS lesions harbour prevalent TP53 or NOTCH1 mutations and that additional somatic mutations and CNAs may lead to cSCC progression in AK/CIS lesions.

Genomic comparison between an in vitro three-dimensional culture model of melanoma and the original primary tumor.

Three-dimensional (3D) melanoma culture is a personalized in vitro model that can be used for high-fidelity pre-clinical testing and validation of novel therapies. However, whether the genomic landscape of 3D cultures faithfully reflects the original primary tumor which remains unknown. The purpose of our study was to compare the genomic landscapes of 3D culture models with those of the original tumors. Patient-derived xenograft (PDX) tumors were established by engrafting fresh melanoma tissue from each patient. Then, a 3D culture model was generated using cryopreserved PDX tumors embedded in pre-gelled porcine skin decellularized extracellular matrix with normal human dermal fibroblasts. Using whole-exome sequencing, the genomic landscapes of 3D cultures, PDX tumors, and the original tumor were compared. We found that 91.4% of single-nucleotide variants in the original tumor were detected in the 3D culture and PDX samples. Putative melanoma driver mutations (BRAF p.V600E, CDKN2A p.R7*, ADAMTS1 p.Q572*) were consistently identified in both the original tumor and 3D culture samples. Genome-wide copy number alteration profiles were almost identical between the original tumor and 3D culture samples, including the driver events of ARID1B loss, BRAF gain, and CCND1 gain. In conclusion, our study revealed that the genomic profiles of the original tumor and our 3D culture model showed high concordance, indicating the reliability of our 3D culture model in reflecting the original characteristics of the tumor.

Genomic landscape of multiple Bowen's disease using whole-exome sequencing.

The genomic landscape of Bowen's disease (BD), with multiple manifestations, has not yet been determined. This study aimed to investigate the genomic alterations in multiple BD. We performed whole-exome sequencing of BD lesions (n = 9) and matched germlines collected from three patients with multiple (≥3) BD to detect somatic and germline mutations. We found a median of 64 somatic mutations in each sample (range 20-267). UV-signature mutations accounted for 64.9% (median, range 26.0%-82.1%) of point mutations. Putative driver mutations were found in five BDs (RB1 p.R445*, ARID2 p.R274*, TP53 p.Y163D/p.Y205D/p.R342*, KMT2C p.R4549C) but not in the other four lesions. Somatic mutations were not shared between multiple BD lesions collected from the same patient, indicating a different clonal origin. We also found no known pathogenic germline mutations in cancer-related genes. The mutational signature analysis revealed that UV signatures (SBS7a/7b) and age-related signatures (SBS1/5) were the main active signatures. Copy number alterations (CNAs) were found in two BDs: one with extensive CNA regions (21.7% of the genome), including driver genes (PIK3CA/SOX2/TP63 and MYC gain, and CDKN2A loss), and the other with 1q gain. Our study revealed that multiple BD lesions harbor distinct genomic landscapes, suggesting that they have different risks of malignant progression.

AS-CMC: a pan-cancer database of alternative splicing for molecular classification of cancer.

Alternative splicing (AS) is a post-transcriptional regulation that leads to the complexity of the transcriptome. Despite the growing importance of AS in cancer research, the role of AS has not been systematically studied, especially in understanding cancer molecular classification. Herein, we analyzed the molecular subtype-specific regulation of AS using The Cancer Genome Atlas data and constructed a web-based database, named Alternative Splicing for Cancer Molecular Classification (AS-CMC). Our system harbors three analysis modules for exploring subtype-specific AS events, evaluating their phenotype association, and performing pan-cancer comparison. The number of subtype-specific AS events was found to be diverse across cancer types, and some differentially regulated AS events were recurrently found in multiple cancer types. We analyzed a subtype-specific AS in exon 11 of mitogen-activated protein kinase kinase 7 (MAP3K7) as an example of a pan-cancer AS biomarker. This AS marker showed significant association with the survival of patients with stomach adenocarcinoma. Our analysis revealed AS as an important determinant for cancer molecular classification. AS-CMC is the first web-based resource that provides a comprehensive tool to explore the biological implications of AS events, facilitating the discovery of novel AS biomarkers.

Rapid and specific detection of Trichophyton rubrum and Trichophyton mentagrophytes using a loop-mediated isothermal amplification assay.

Trichophyton rubrum and Trichophyton mentagrophytes are the main causative pathogens of onychomycosis. However, the sensitivity and specificity of conventional microscopic tests are insufficient for reliable diagnoses of onychomycosis. In this study, we developed loop-mediated isothermal amplification (LAMP) assays for the rapid and specific identification of the two major Trichophytons spp. We designed LAMP primers targeting the internal transcribed spacer 1 region of the T. rubrum and T. mentagrophytes. Through rigorous optimization of the reaction conditions, we defined a universal reaction condition for both LAMP assays.