Single-cell characterization of malignant phenotypes and microenvironment alteration in retinoblastoma

The role of lactate metabolism in retinoblastoma tumorigenesis and ferroptosis resistance

The Warburg effect, a hallmark of cancer, describes the preference of cancer cells for glucose metabolism via aerobic glycolysis, leading to substantial lactate accumulation. However, the role of lactate metabolism in retinoblastoma, the primary intraocular malignancy in children, remains unclear. This study aimed to elucidate the gene expression profiles associated with lactate metabolism in retinoblastoma and their impact on tumorigenesis and ferroptosis resistance. The involvement of metabolic characteristics in retinoblastoma was analyzed by comparing single-cell RNA sequencing transcriptome profiles from normal retina tissues and retinoblastoma tissues from patient samples. The effects of lactate on retinoblastoma cell line viability and its mechanisms were examined both in vitro and in vivo. Single-cell RNA sequencing analysis revealed enhanced glycolysis in retinoblastoma cells and significant differences in lactate metabolism-related gene expression among various retinoblastoma cell types. Retinoblastoma cell lines with moderate lactate levels exhibited increased viability and resistance to ferroptosis induced by ferroptosis inducers. Additionally, lactate promoted the upregulation of monocarboxylate transporter 1 (MCT1), which facilitated lactate transport, in a dose-dependent manner in retinoblastoma cell lines. Knocking down MCT1 reduced both viability and ferroptosis resistance of retinoblastoma cell lines in a lactate-rich environment. In vivo, disrupting lactate transport through MCT1 inhibition suppressed retinoblastoma tumorigenesis and invasion in a mouse xenograft model, and this effect was reversed by the ferroptosis inhibitor liproxstatin-1. These findings highlighted the crucial role of lactate metabolism in retinoblastoma tumorigenesis and resistance to ferroptosis.

Single-cell transcriptomic analyses provide insights into the tumor microenvironment heterogeneity and invasion phenotype in retinoblastoma

BACKGROUND

As the most common intraocular malignant tumor, retinoblastoma (RB) is associated with high mortality during early childhood. The heterogeneous cellular composition of the tumor microenvironment (TME) plays a pivotal role in modulating immune responses, tumor growth and metastasis progression. However, the landscape of TME heterogeneity and cell-cell communication networks in RB remain poorly characterized.

METHODS

Different phenotypes of RB were characterized by integrated single-cell sequencing data. Cellular subclusters of three principal TME components were systematically identified. CellChat analyzed package was employed to depict intercellular communications across all types of cells in TME. Next, pseudotime trajectory analyses were performed with Monocle package. CIBERSORT algorithms (LM22 signature matrix) and CIBERSORTx platform were employed to characterize immune cell infiltration landscape from microarray data. Finally, functional enrichment profiling elucidated associations between TME subcluster signatures and extraocular invasion phenotypes of RB.

RESULTS

Characteristic subclusters of TME components, such as MG1 in tumor-associated macrophages (TAMs) and AC1 in astrocyte-like cells were probably associated with RB extraocular invasion in different ways. And RB invasive progression might be relevant with the cell-cell communications landscape change between TME-related cell populations. Trajectory analysis revealed the potential correlation of RB invasion with the increase of immature TAMs and the decrease of terminally differentiated astrocyte-like cells. Functional enrichment analysis further profiled the distinct molecular feature of characteristic subclusters.

CONCLUSIONS

This study systematically delineates TME heterogeneity landscapes across non-invasive versus invasive RB, providing mechanistic insights into intercellular communications within TME. Our findings might have the potential to develop microenvironment-targeted therapeutic strategies in RB management.

SOX4 as a Key Oncogene Driving Tumor Invasion in Retinoblastoma

Purpose

This study aims to explore the role of SRY-related HMG box transcription factor 4 (SOX4) in promoting invasion in retinoblastoma (RB) and to elucidate the underlying oncogenic pathways.

Methods

SOX4 expression in human retina, intraocular RB, and extraocular RB samples was evaluated using bulk RNA sequencing (RNA-seq) and single-cell RNA sequencing (scRNA-seq), with further evaluation in RB cell lines (Y79, WERI-RB1). Small interfering RNA-mediated knockdown was performed in RB cell lines, followed by functional assays including CCK-8, EdU, colony formation, and transwell assays. An orthotopic xenograft model with SOX4 knockdown was utilized to assess tumor invasion. RNA-seq was performed on SOX4 knockdown (si-SOX4) and control (si-NC) Y79 cells to explore downstream signaling pathways.

Results

RNA-seq and scRNA-seq data revealed that SOX4, E2F3, and DEK were significantly upregulated in RB tissues compared to normal retina. Notably, SOX4 expression was particularly elevated in extraocular RB tissues, especially in MKI67+ photoreceptorness-decreased cells. Knockdown of SOX4 in RB cell lines caused decreased proliferation, colony formation, migration, and reversal of epithelial-to-mesenchymal transition markers (N-cadherin, E-cadherin, vimentin). In vivo, SOX4 knockdown resulted in fewer cases of anterior chamber involvement and eyeball wall invasion in an orthotopic xenograft model. RNA-seq analysis revealed that SOX4 knockdown altered the Wnt/β-catenin and cyclin D1 signaling pathways.

Conclusions

SOX4 plays a critical role in driving local invasion in RB, and targeting SOX4 may provide new insights into the molecular mechanisms of RB invasion, potentially leading to improved therapeutic strategies for RB treatment.

Tumor heterogeneity in retinoblastoma: a literature review

Tumor heterogeneity, characterized by the presence of diverse cell populations within a tumor, is a key feature of the complex nature of cancer. This diversity arises from the emergence of cells with varying genomic, epigenetic, transcriptomic, and phenotypic profiles over the course of the disease. Host factors and the tumor microenvironment play crucial roles in driving both inter-patient and intra-patient heterogeneity. These diverse cell populations can exhibit different behaviors, such as varying rates of proliferation, responses to treatment, and potential for metastasis. Both inter-patient heterogeneity and intra-patient heterogeneity pose significant challenges to cancer therapeutics and management. In retinoblastoma, while heterogeneity at the clinical presentation level has been recognized for some time, recent attention has shifted towards understanding the underlying cellular heterogeneity. This review primarily focuses on retinoblastoma heterogeneity and its implications for therapeutic strategies and disease management, emphasizing the need for further research and exploration in this complex and challenging area.

The Role of Small Extracellular Vesicles in Retinoblastoma Development and Progression

A growing body of research on extracellular vesicles (EVs) in cancer has revealed their novel and crucial activities in the progression of tumors while also paving the way for potential therapeutic interventions. It is now known that EVs are natural delivery vehicles for particular payloads of source cells, enabling them to influence diverse functions of cells both in healthy and malignant cells. In this review, we comprehensively summarize mechanistic insights into sEV roles in RB, the most frequent intraocular malignancy that affects the retina of young children. We also explore the therapeutic potential of sEVs as an emerging area as biomarkers and vehicles for targeted therapy. Additionally, we address the potential challenges and limitations of translating sEVs-based technologies into clinical practice.

Identification and validation of glycolysis-related diagnostic signatures in diabetic nephropathy: a study based on integrative machine learning and single-cell sequence

Background

Diabetic nephropathy (DN) is a complication of systemic microvascular disease in diabetes mellitus. Abnormal glycolysis has emerged as a potential factor for chronic renal dysfunction in DN. The current lack of reliable predictive biomarkers hinders early diagnosis and personalized therapy.

Methods

Transcriptomic profiles of DN samples and controls were extracted from GEO databases. Differentially expressed genes (DEGs) and their functional enrichments were identified. Glycolysis-related genes (GRGs) were selected by combining DEGs, weighted gene co-expression network, and glycolysis candidate genes. We established a diagnostic signature termed GScore via integrative machine learning framework. The diagnostic efficacy was evaluated by decision curve and calibration curve. Single-cell RNA sequence data was used to identify cell subtypes and interactive signals. The cMAP database was used to find potential therapeutic agents targeting GScore for DN. The expression levels of diagnostic signatures were verified in vitro.

Results

Through the 108 combinations of machine learning algorithms, we selected 12 diagnostic signatures, including CD163, CYBB, ELF3, FCN1, PROM1, GPR65, LCN2, LTF, S100A4, SOX4, TGFB1 and TNFAIP8. Based on them, an integrative model named GScore was established for predicting DN onset and stratifying clinical risk. We observed distinct biological characteristics and immunological microenvironment states between the high-risk and low-risk groups. GScore was significantly associated with neutrophils and non-classical monocytes. Potential agents including esmolol, estradiol, ganciclovir, and felbamate, targeting the 12 diagnostic signatures were identified. In vitro, ELF3, LCN2 and CD163 were induced in high glucose-induced HK-2 cell lines.

Conclusion

An integrative machine learning frame established a novel diagnostic signature using glycolysis-related genes. This study provides a new direction for the early diagnosis and treatment of DN.

Oncolytic Viruses and Immunotherapy for the Treatment of Uveal Melanoma and Retinoblastoma: The Current Landscape and Novel Advances

Intraocular malignant tumors are rare; however, they can cause serious life-threatening complications. Uveal melanoma (UM) and retinoblastoma (RB) are the most common intraocular tumors in adults and children, respectively, and come with a great disease burden. For many years, several different treatment modalities for UM and RB have been proposed, with chemotherapy for RB cases and plaque radiation therapy for localized UM as first-line treatment options. Extraocular extension, recurrence, and metastasis constitute the major challenges of conventional treatments. To overcome these obstacles, immunotherapy, which encompasses different treatment options such as oncolytic viruses, antibody-mediated immune modulations, and targeted immunotherapy, has shown great potential as a novel therapeutic tool for cancer therapy. These anti-cancer treatment options provide numerous advantages such as selective cancer cell death and the promotion of an anti-tumor immune response, and they prove useful in preventing vision impairment due to macular and/or optic disc involvement. Numerous factors such as the vector choice, route of administration, dosing, and patient characteristics must be considered when engineering an oncolytic virus or other forms of immunotherapy vectors. This manuscript provides an in-depth review of the molecular design of oncolytic viruses (e.g., virus capsid proteins and encapsulation technologies, vectors for delivery, cell targeting) and immunotherapy. The most recent advances in preclinical- and clinical-phase studies are further summarized. The recent developments in virus-like drug conjugates (i.e., AU011), oncolytic viruses for metastatic UM, and targeted immunotherapies have shown great results in clinical trials for the future clinical application of these novel technologies in the treatment algorithm of certain intraocular tumors.

In vitro model of retinoblastoma derived tumor and stromal cells for tumor microenvironment (TME) studies

Retinoblastoma (RB) is an intraocular tumor arising from retinal cone progenitor cells affecting young children. In the last couple of years, RB treatment evolved towards eye preserving therapies. Therefore, investigating intratumoral differences and the RB tumor microenvironment (TME), regulating tumorigenesis and metastasis, is crucial. How RB cells and their TME are involved in tumor development needs to be elucidated using in vitro models including RB derived stromal cells. In the study presented, we established primary RB derived tumor and stromal cell cultures and compared them by RNAseq analysis to identify their gene expression signatures. RB tumor cells cultivated in serum containing medium were more differentiated compared to RB tumor cells grown in serum-free medium displaying a stem cell like phenotype. In addition, we identified differentially expressed genes for RB tumor and stromal derived cells. Furthermore, we immortalized cells of a RB1 mutated, MYCN amplified and trefoil factor family peptid 1 (TFF1) positive RB tumor and RB derived non-tumor stromal tissue. We characterized both immortalized cell lines using a human oncology proteome array, immunofluorescence staining of different markers and in vitro cell growth analyses. Tumor formation of the immortalized RB tumor cell line was investigated in a chicken chorioallantoic membrane (CAM) model. Our studies revealed that the RB stromal derived cell line comprises tumor associated macrophages (TAMs), glia and cancer associated fibroblasts (CAFs), we were able to successfully separate via magnetic cell separation (MACS). For co-cultivation studies, we established a 3D spheroid model with RB tumor and RB derived stromal cells. In summary, we established an in vitro model system to investigate the interaction of RB tumor cells with their TME. Our findings contribute to a better understanding of the relationship between RB tumor malignancy and its TME and will facilitate the development of effective treatment options for eye preserving therapies.

Targeting ALDOA to modulate tumorigenesis and energy metabolism in retinoblastoma

This study aims to elucidate the pivotal role of aldolase A (ALDOA) in retinoblastoma (RB) and evaluate the potential of the ALDOA inhibitor itaconate in impeding RB progression. Utilizing single-cell RNA sequencing, ALDOA consistently exhibits overexpression across diverse cell types, particularly in cone precursor cells, retinoma-like cells, and retinoblastoma-like cells. This heightened expression is validated in RB tissues and cell lines. ALDOA knockdown significantly diminishes RB cell viability, impedes colony formation, and induces notable metabolic alterations. RNA-seq analysis identifies SUSD2, ARHGAP27, and CLK2 as downstream genes associated with ALDOA. The application of itaconate demonstrates efficacy in inhibiting RB cell proliferation, validated through in vitro and in vivo models. This study emphasizes ALDOA as a promising target for innovative RB therapies, with potential implications for altering tumor energy metabolism.

Comprehensive identification of pathogenic variants in retinoblastoma by long- and short-read sequencing

Retinoblastoma (RB) is the most common intraocular malignancy in childhood. The causal variants in RB are mostly characterized by previously used short-read sequencing (SRS) analysis, which has technical limitations in identifying structural variants (SVs) and phasing information. Long-read sequencing (LRS) technology has advantages over SRS in detecting SVs, phased genetic variants, and methylation. In this study, we comprehensively characterized the genetic landscape of RB using combinatorial LRS and SRS of 16 RB tumors and 16 matched blood samples. We detected a total of 232 somatic SVs, with an average of 14.5 SVs per sample across the whole genome in our cohort. We identified 20 distinct pathogenic variants disrupting RB1 gene, including three novel small variants and five somatic SVs. We found more somatic SVs were detected from LRS than SRS (140 vs. 122) in RB samples with WGS data, particularly the insertions (18 vs. 1). Furthermore, our analysis shows that, with the exception of one sample who lacked the methylation data, all samples presented biallelic inactivation of RB1 in various forms, including two cases with the biallelic hypermethylated promoter and four cases with compound heterozygous mutations which were missing in SRS analysis. By inferring relative timing of somatic events, we reveal the genetic progression that RB1 disruption early and followed by copy number changes, including amplifications of Chr2p and deletions of Chr16q, during RB tumorigenesis. Altogether, we characterize the comprehensive genetic landscape of RB, providing novel insights into the genetic alterations and mechanisms contributing to RB initiation and development. Our work also establishes a framework to analyze genomic landscape of cancers based on LRS data.

Single-cell RNA-Seq reveals the heterogeneity of fibroblasts within the tympanojugular paraganglioma microenvironment

Tympanojugular paragangliomas (TJP) originate from the parasympathetic ganglia in the lateral base of the skull. Although the cellular composition and oncogenic mechanisms of paragangliomas have been evaluated, a comprehensive transcriptomic atlas specific to TJP remains to be established to facilitate further investigations. In this study, single-cell RNA sequencing and whole-exome sequencing were conducted on six surgically excised TJP samples to determine their cellular composition and intratumoral heterogeneity. Fibroblasts were sub-classified into two distinct groups: myofibroblasts and fibroblasts associated with bone remodeling. Additionally, an elaborate regulatory and cell-cell communication network was determined, highlighting the multifaceted role of fibroblasts, which varies depending on expression transitions. The Kit receptor (KIT) signaling pathway mediated interactions between fibroblasts and mast cells, whereas robust connections with endothelial and Schwann cell-like cells were facilitated through the platelet-derived growth factor signaling pathway. These findings establish a foundation for studying the mechanisms underlying protumor angiogenesis and the specific contributions of fibroblasts within the TJP microenvironment. IL6 signaling pathway of fibroblasts interacting with macrophages and endothelial cells may be involved in tumor regrowth. These results enhance our understanding of fibroblast functionality and provide a resource for future therapeutic targeting of TJP.

Focused cancer pathway analysis revealed unique therapeutic targets in retinoblastoma

Retinoblastoma (RB) is a pediatric cancer of the eye that occurs in 1/15000 live births worldwide. Albeit RB is initiated by the inactivation of RB1 gene, the disease progression relies largely on transcriptional alterations. Therefore, evaluating gene expression is vital to unveil the therapeutic targets in RB management. In this study, we employed an RT2 Profiler™ PCR array for a focused analysis of 84 cancer-specific genes in RB. An interaction network was built with gene expression data to identify the dysregulated pathways in RB. The key transcript alterations identified in 13 tumors by RT2 Profiler™ PCR array was further validated in 15 tumors by independent RT-qPCR. Out of 84 cancer-specific genes, 68 were dysregulated in RB tumors. Among the 68 genes, 23 were chosen for further analysis based on statistical significance and abundance across multiple tumors. Pathway analysis of altered genes showed the frequent perturbations of cell cycle, angiogenesis and apoptotic pathways in RB. Notably, upregulation of MCM2, MKI67, PGF, WEE1, CDC20 and downregulation of COX5A were found in all the tumors. Western blot confirmed the dysregulation of identified targets at protein levels as well. These alterations were more prominent in invasive RB, correlating with the disease pathogenesis. Our molecular analysis thus identified the potential therapeutic targets for improving retinoblastoma treatment. We also suggest that PCR array can be used as a tool for rapid and cost-effective gene expression analysis.

Deciphering metabolic heterogeneity in retinoblastoma unravels the role of monocarboxylate transporter 1 in tumor progression

BACKGROUND

Tumors exhibit metabolic heterogeneity, influencing cancer progression. However, understanding metabolic diversity in retinoblastoma (RB), the primary intraocular malignancy in children, remains limited.

METHODS

The metabolic landscape of RB was constructed based on single-cell transcriptomic sequencing from 11 RB and 5 retina samples. Various analyses were conducted, including assessing overall metabolic activity, metabolic heterogeneity, and the correlation between hypoxia and metabolic pathways. Additionally, the expression pattern of the monocarboxylate transporter (MCT) family in different cell clusters was examined. Validation assays of MCT1 expression and function in RB cell lines were performed. The therapeutic potential of targeting MCT1 was evaluated using an orthotopic xenograft model. A cohort of 47 RB patients was analyzed to evaluate the relationship between MCT1 expression and tumor invasion.

RESULTS

Distinct metabolic patterns in RB cells, notably increased glycolysis, were identified. This metabolic heterogeneity correlated closely with hypoxia. MCT1 emerged as the primary monocarboxylate transporter in RB cells. Disrupting MCT1 altered cell viability and energy metabolism. In vivo studies using the MCT1 inhibitor AZD3965 effectively suppressed RB tumor growth. Additionally, a correlation between MCT1 expression and optic nerve invasion in RB samples suggested prognostic implications.

CONCLUSIONS

This study enhances our understanding of RB metabolic characteristics at the single-cell level, highlighting the significance of MCT1 in RB pathogenesis. Targeting MCT1 holds promise as a therapeutic strategy for combating RB, with potential prognostic implications.

Pediatric Solid Cancers: Dissecting the Tumor Microenvironment to Improve the Results of Clinical Immunotherapy

Despite advances in their diagnosis and treatment, pediatric cancers remain among the leading causes of death in childhood. The development of immunotherapies and other forms of targeted therapies has significantly changed the prognosis of some previously incurable cancers in the adult population. However, so far, the results in pediatric cohorts are disappointing, which is mainly due to differences in tumor biology, including extreme heterogeneity and a generally low tumor mutational burden. A central role in the limited efficacy of immunotherapeutic approaches is played by the peculiar characteristics of the tumor microenvironment (TME) in pediatric cancer, with the scarcity of tumor infiltration by T cells and the abundance of stromal cells endowed with lymphocyte suppressor and tumor-growth-promoting activity. Thus, progress in the treatment of pediatric solid tumors will likely be influenced by the ability to modify the TME while delivering novel, more effective therapeutic agents. In this review, we will describe the TME composition in pediatric solid tumors and illustrate recent advances in treatment for the modulation of immune cells belonging to the TME.

Recent progress in retinoblastoma: Pathogenesis, presentation, diagnosis and management

Retinoblastoma, the primary ocular malignancy in pediatric patients, poses a substantial threat to mortality without prompt and effective management. The prognosis for survival and preservation of visual acuity hinges upon the disease severity at the time of initial diagnosis. Notably, retinoblastoma has played a crucial role in unraveling the genetic foundations of oncogenesis. The process of tumorigenesis commonly begins with the occurrence of biallelic mutation in the RB1 tumor suppressor gene, which is then followed by a cascade of genetic and epigenetic alterations that correspond to the clinical stage and pathological features of the tumor. The RB1 gene, recognized as a tumor suppressor, encodes the retinoblastoma protein, which plays a vital role in governing cellular replication through interactions with E2F transcription factors and chromatin remodeling proteins. The diagnosis and treatment of retinoblastoma necessitate consideration of numerous factors, including disease staging, germline mutation status, family psychosocial factors, and the resources available within the institution. This review has systematically compiled and categorized the latest developments in the diagnosis and treatment of retinoblastoma which enhanced the quality of care for this pediatric malignancy.

Single-cell disulfidptosis regulator patterns guide intercellular communication of tumor microenvironment that contribute to kidney renal clear cell carcinoma progression and immunotherapy

Background

Disulfidptosis, an emerging type of programmed cell death, plays a pivotal role in various cancer types, notably impacting the progression of kidney renal clear cell carcinoma (KIRC) through the tumor microenvironment (TME). However, the specific involvement of disulfidptosis within the TME remains elusive.

Methods

Analyzing 41,784 single cells obtained from seven samples of KIRC through single-cell RNA sequencing (scRNA-seq), this study employed nonnegative matrix factorization (NMF) to assess 24 disulfidptosis regulators. Pseudotime analysis, intercellular communication mapping, determination of transcription factor activities (TFs), and metabolic profiling of the TME subgroup in KIRC were conducted using Monocle, CellChat, SCENIC, and scMetabolism. Additionally, public cohorts were utilized to predict prognosis and immune responses within the TME subgroup of KIRC.

Results

Through NMF clustering and differential expression marker genes, fibroblasts, macrophages, monocytes, T cells, and B cells were categorized into four to six distinct subgroups. Furthermore, this investigation revealed the correlation between disulfidptosis regulatory factors and the biological traits, as well as the pseudotime trajectories of TME subgroups. Notably, disulfidptosis-mediated TME subgroups (DSTN+CD4T-C1 and FLNA+CD4T-C2) demonstrated significant prognostic value and immune responses in patients with KIRC. Multiple immunohistochemistry (mIHC) assays identified marker expression within both cell clusters. Moreover, CellChat analysis unveiled diverse and extensive interactions between disulfidptosis-mediated TME subgroups and tumor epithelial cells, highlighting the TNFSF12-TNFRSF12A ligand-receptor pair as mediators between DSTN+CD4T-C1, FLNA+CD4T-C2, and epithelial cells.

Conclusion

Our study sheds light on the role of disulfidptosis-mediated intercellular communication in regulating the biological characteristics of the TME. These findings offer valuable insights for patients with KIRC, potentially guiding personalized immunotherapy approaches.

Single-cell transcriptomics enable the characterization of local extension in retinoblastoma

Retinoblastoma (RB) is the most prevalent ocular tumor of childhood, and its extraocular invasion significantly increases the risk of metastasis. Nevertheless, a single-cell characterization of RB local extension has been lacking. Here, we perform single-cell RNA sequencing on four RB samples (two from intraocular and two from extraocular RB patients), and integrate public datasets of five normal retina samples, four intraocular samples, and three extraocular RB samples to characterize RB local extension at the single-cell level. A total of 128,454 qualified cells are obtained in nine major cell types. Copy number variation inference reveals chromosome 6p amplification in cells derived from extraocular RB samples. In cellular heterogeneity analysis, we identified 10, 8, and 7 cell subpopulations in cone precursor like cells, retinoma like cells, and MKI67+ photoreceptorness decreased (MKI67+ PhrD) cells, respectively. A high expression level of SOX4 was detected in cells from extraocular samples, especially in MKI67+ PhrD cells, which was verified in additional clinical RB samples. These results suggest that SOX4 might drive RB local extension. Our study presents a single-cell transcriptomic landscape of intraocular and extraocular RB samples, improving our understanding of RB local extension at the single-cell resolution and providing potential therapeutic targets for RB patients.

Heterogeneous Expression Patterns of the Minichromosome Maintenance Complex Members in Retinoblastoma Unveil Its Clinical Significance

Purpose

To explore the expression patterns and clinical significance of minichromosome maintenance (MCM) complex members in retinoblastoma (RB).

Methods

Single-cell RNA sequencing datasets from five normal retina, six intraocular, and five extraocular RB samples were integrated to characterize the expression patterns of MCM complex members at the single-cell level. Western blot and quantitative PCR were used to detect the expression of MCM complex members in RB cell lines. Immunohistochemistry was conducted to validate the expression of MCM complex members in RB patient samples and a RB mouse model.

Results

The expression of MCM2-7 is increased in RB tissue, with MCM2/3/7 showing particularly higher levels in extraocular RB. MCM3/7 are abundantly detected in cell types associated with oncogenesis. Both mRNA and protein levels of MCM3/4/6/7 are increased in RB cell lines. Immunohistochemistry further confirmed the elevated expression of MCM3 in extraocular RB, with MCM6 being the most abundantly expressed MCM in RB.

Conclusions

The distinct MCM expression patterns across various RB cell types suggest diverse functional roles, offering valuable insights for targeted therapeutic strategies. The upregulation of MCM3, MCM4, MCM6, and MCM7 in RB, with a specific emphasis on MCM6 as a notable marker, highlights their potential significance.

Transcriptome analysis reveals molecularly distinct subtypes in retinoblastoma

Retinoblastoma is the most frequent intraocular malignancy in children. Little is known on the molecular basis underlying the biological and clinical behavior of this cancer. Here, using gene expression profiles, we demonstrate the existence of two major retinoblastoma subtypes that can be divided into six subgroups. Subtype 1 has higher expression of cone related genes and higher percentage of RB1 germline mutation. By contrast, subtype 2 tumors harbor more genes with ganglion/neuronal features. The dedifferentiation in subtype 2 is associated with stemness features including low immune infiltration. Gene Otology analysis demonstrates that immune response regulations and visual related pathways are the key molecular difference between subtypes. Subtype 1b has the highest risk of invasiveness across all subtypes. The recognition of these molecular subtypes shed a light on the important biological and clinical perspectives for retinoblastomas.

Oncogenic Proteomics Approaches for Translational Research and HIV-Associated Malignancy Mechanisms

Recent advances in the field of proteomics have allowed extensive insights into the molecular regulations of the cell proteome. Specifically, this allows researchers to dissect a multitude of signaling arrays while targeting for the discovery of novel protein signatures. These approaches based on data mining are becoming increasingly powerful for identifying both potential disease mechanisms as well as indicators for disease progression and overall survival predictive and prognostic molecular markers for cancer. Furthermore, mass spectrometry (MS) integrations satisfy the ongoing demand for in-depth biomarker validation. For the purpose of this review, we will highlight the current developments based on MS sensitivity, to place quantitative proteomics into clinical settings and provide a perspective to integrate proteomics data for future applications in cancer precision medicine. We will also discuss malignancies associated with oncogenic viruses such as Acquire Immunodeficiency Syndrome (AIDS) and suggest novel mechanisms behind this phenomenon. Human Immunodeficiency Virus type-1 (HIV-1) proteins are known to be oncogenic per se, to induce oxidative and endoplasmic reticulum stresses, and to be released from the infected or expressing cells. HIV-1 proteins can act alone or in collaboration with other known oncoproteins, which cause the bulk of malignancies in people living with HIV-1 on ART.

Single-cell sequencing in primary intraocular tumors: understanding heterogeneity, the microenvironment, and drug resistance

Retinoblastoma (RB) and uveal melanoma (UM) are the most common primary intraocular tumors in children and adults, respectively. Despite continued increases in the likelihood of salvaging the eyeball due to advancements in local tumor control, prognosis remains poor once metastasis has occurred. Traditional sequencing technology obtains averaged information from pooled clusters of diverse cells. In contrast, single-cell sequencing (SCS) allows for investigations of tumor biology at the resolution of the individual cell, providing insights into tumor heterogeneity, microenvironmental properties, and cellular genomic mutations. SCS is a powerful tool that can help identify new biomarkers for diagnosis and targeted therapy, which may in turn greatly improve tumor management. In this review, we focus on the application of SCS for evaluating heterogeneity, microenvironmental characteristics, and drug resistance in patients with RB and UM.

Artificial intelligence in cancer immunotherapy: Applications in neoantigen recognition, antibody design and immunotherapy response prediction

Cancer immunotherapy is a method of controlling and eliminating tumors by reactivating the body's cancer-immunity cycle and restoring its antitumor immune response. The increased availability of data, combined with advancements in high-performance computing and innovative artificial intelligence (AI) technology, has resulted in a rise in the use of AI in oncology research. State-of-the-art AI models for functional classification and prediction in immunotherapy research are increasingly used to support laboratory-based experiments. This review offers a glimpse of the current AI applications in immunotherapy, including neoantigen recognition, antibody design, and prediction of immunotherapy response. Advancing in this direction will result in more robust predictive models for developing better targets, drugs, and treatments, and these advancements will eventually make their way into the clinical setting, pushing AI forward in the field of precision oncology.