Glioblastoma evolution and heterogeneity from a 3D whole-tumor perspective.

Treatment failure for the lethal brain tumor glioblastoma (GBM) is attributed to intratumoral heterogeneity and tumor evolution. We utilized 3D neuronavigation during surgical resection to acquire samples representing the whole tumor mapped by 3D spatial coordinates. Integrative tissue and single-cell analysis revealed sources of genomic, epigenomic, and microenvironmental intratumoral heterogeneity and their spatial patterning. By distinguishing tumor-wide molecular features from those with regional specificity, we inferred GBM evolutionary trajectories from neurodevelopmental lineage origins and initiating events such as chromothripsis to emergence of genetic subclones and spatially restricted activation of differential tumor and microenvironmental programs in the core, periphery, and contrast-enhancing regions. Our work depicts GBM evolution and heterogeneity from a 3D whole-tumor perspective, highlights potential therapeutic targets that might circumvent heterogeneity-related failures, and establishes an interactive platform enabling 360° visualization and analysis of 3D spatial patterns for user-selected genes, programs, and other features across whole GBM tumors.

Analysis of 3D pathology samples using weakly supervised AI.

Human tissue, which is inherently three-dimensional (3D), is traditionally examined through standard-of-care histopathology as limited two-dimensional (2D) cross-sections that can insufficiently represent the tissue due to sampling bias. To holistically characterize histomorphology, 3D imaging modalities have been developed, but clinical translation is hampered by complex manual evaluation and lack of computational platforms to distill clinical insights from large, high-resolution datasets. We present TriPath, a deep-learning platform for processing tissue volumes and efficiently predicting clinical outcomes based on 3D morphological features. Recurrence risk-stratification models were trained on prostate cancer specimens imaged with open-top light-sheet microscopy or microcomputed tomography. By comprehensively capturing 3D morphologies, 3D volume-based prognostication achieves superior performance to traditional 2D slice-based approaches, including clinical/histopathological baselines from six certified genitourinary pathologists. Incorporating greater tissue volume improves prognostic performance and mitigates risk prediction variability from sampling bias, further emphasizing the value of capturing larger extents of heterogeneous morphology.

Interfaces of Malignant and Immunologic Clonal Dynamics in Ovarian Cancer.

High-grade serous ovarian cancer (HGSC) exhibits extensive malignant clonal diversity with widespread but non-random patterns of disease dissemination. We investigated whether local immune microenvironment factors shape tumor progression properties at the interface of tumor-infiltrating lymphocytes (TILs) and cancer cells. Through multi-region study of 212 samples from 38 patients with whole-genome sequencing, immunohistochemistry, histologic image analysis, gene expression profiling, and T and B cell receptor sequencing, we identified three immunologic subtypes across samples and extensive within-patient diversity. Epithelial CD8+ TILs negatively associated with malignant diversity, reflecting immunological pruning of tumor clones inferred by neoantigen depletion, HLA I loss of heterozygosity, and spatial tracking between T cell and tumor clones. In addition, combinatorial prognostic effects of mutational processes and immune properties were observed, illuminating how specific genomic aberration types associate with immune response and impact survival. We conclude that within-patient spatial immune microenvironment variation shapes intraperitoneal malignant spread, provoking new evolutionary perspectives on HGSC clonal dispersion.

A multi-omic single-cell landscape of human gynecologic malignancies.

Deconvolution of regulatory mechanisms that drive transcriptional programs in cancer cells is key to understanding tumor biology. Herein, we present matched transcriptome (scRNA-seq) and chromatin accessibility (scATAC-seq) profiles at single-cell resolution from human ovarian and endometrial tumors processed immediately following surgical resection. This dataset reveals the complex cellular heterogeneity of these tumors and enabled us to quantitatively link variation in chromatin accessibility to gene expression. We show that malignant cells acquire previously unannotated regulatory elements to drive hallmark cancer pathways. Moreover, malignant cells from within the same patients show substantial variation in chromatin accessibility linked to transcriptional output, highlighting the importance of intratumoral heterogeneity. Finally, we infer the malignant cell type-specific activity of transcription factors. By defining the regulatory logic of cancer cells, this work reveals an important reliance on oncogenic regulatory elements and highlights the ability of matched scRNA-seq/scATAC-seq to uncover clinically relevant mechanisms of tumorigenesis in gynecologic cancers.

Epigenetic escape of immunosurveillance by malignant cell precursors.

Newly formed malignant cells must escape immunosurveillance to generate progressing neoplastic lesions of clinical relevance. Recent data indicate that the immunogenicity of nascent cancer cells, at least in some settings, is dictated by inherent epigenetic mechanisms rather than by immunoediting and the consequent Darwinian selection of poorly immunogenic phenotypes.

SETD2 safeguards the genome against isochromosome formation.

Isochromosomes are mirror-imaged chromosomes with simultaneous duplication and deletion of genetic material which may contain two centromeres to create isodicentric chromosomes. Although isochromosomes commonly occur in cancer and developmental disorders and promote genome instability, mechanisms that prevent isochromosomes are not well understood. We show here that the tumor suppressor and methyltransferase SETD2 is essential to prevent these errors. Using cellular and cytogenetic approaches, we demonstrate that loss of SETD2 or its epigenetic mark, histone H3 lysine 36 trimethylation (H3K36me3), results in the formation of isochromosomes as well as isodicentric and acentric chromosomes. These defects arise during DNA replication and are likely due to faulty homologous recombination by RAD52. These data provide a mechanism for isochromosome generation and demonstrate that SETD2 and H3K36me3 are essential to prevent the formation of this common mutable chromatin structure known to initiate a cascade of genomic instability in cancer.

Single-cell transcriptome analysis reveals subtype-specific clonal evolution and microenvironmental changes in liver metastasis of pancreatic adenocarcinoma and their clinical implications.

BACKGROUND: Intratumoral heterogeneity (ITH) and tumor microenvironment (TME) of pancreatic ductal adenocarcinoma (PDAC) play important roles in tumor evolution and patient outcomes. However, the precise characterization of diverse cell populations and their crosstalk associated with PDAC progression and metastasis is still challenging. METHODS: We performed single-cell RNA sequencing (scRNA-seq) of treatment-naïve primary PDAC samples with and without paired liver metastasis samples to understand the interplay between ITH and TME in the PDAC evolution and its clinical associations. RESULTS: scRNA-seq analysis revealed that even a small proportion (22%) of basal-like malignant ductal cells could lead to poor chemotherapy response and patient survival and that epithelial-mesenchymal transition programs were largely subtype-specific. The clonal homogeneity significantly increased with more prevalent and pronounced copy number gains of oncogenes, such as KRAS and ETV1, and losses of tumor suppressor genes, such as SMAD2 and MAP2K4, along PDAC progression and metastasis. Moreover, diverse immune cell populations, including naïve SELLhi regulatory T cells (Tregs) and activated TIGIThi Tregs, contributed to shaping immunosuppressive TMEs of PDAC through cellular interactions with malignant ductal cells in PDAC evolution. Importantly, the proportion of basal-like ductal cells negatively correlated with that of immunoreactive cell populations, such as cytotoxic T cells, but positively correlated with that of immunosuppressive cell populations, such as Tregs. CONCLUSION: We uncover that the proportion of basal-like subtype is a key determinant for chemotherapy response and patient outcome, and that PDAC clonally evolves with subtype-specific dosage changes of cancer-associated genes by forming immunosuppressive microenvironments in its progression and metastasis.

Comparison of Primary and Metastatic Fumarate Hydratase-Deficient Renal Cell Carcinomas Documents Morphologic Divergence and Potential Diagnostic Pitfall With Peritoneal Mesothelioma.

Fumarate hydratase (FH)-deficient renal cell carcinomas are rare neoplasms characterized by wide morphologic heterogeneity and pathogenetic mutations in the FH gene. They often show aggressive behavior with rapid diffusion to distant organs, so novel therapeutic scenarios have been explored, including EGFR inhibitors and PD-L1 expression for targeted immunotherapy. Herein, we investigated a series of 11 primary FH-deficient renal cell carcinomas and 7 distant metastases to evaluate tumor heterogeneity even in metastatic sites and estimate the specific spread rates to various organs. Furthermore, the tumors were tested for immunohistochemical PD-L1 expression and EGFR mutations. Most metastatic cases involved the abdominal lymph nodes (4/7; 57%), followed by the peritoneum (3/7; 42%), the liver (2/7; 29%), and the lungs (1/7; 14%). Six metastatic localizations were histologically documented, revealing a morphologic heterogeneous architecture often differing from that of the corresponding primary renal tumor. Peritoneal involvement morphologically resembled a benign reactive mesothelial process or primary peritoneal mesothelioma, thus advocating to perform an accurate immunohistochemical panel, including PAX8 and FH, to reach a proper diagnosis. A pure low-grade succinate dehydrogenase-looking primary FH-deficient renal cell carcinoma was also recorded. As for therapy, significant PD-L1 labeling was found in 60% of primary renal tumors, whereas none of them carried pathogenetic EGFR mutations. Our data show that FH-deficient renal cell carcinoma may be morphologically heterogeneous in metastases as well, which involve the lymph nodes, the liver, and the peritoneum more frequently than other renal tumors. Due to the high frequency of this latter (42%), pathologists should always be concerned about ruling out mesothelial-derived mimickers, and the occurrence of rarer, primary, low-grade-looking types. Finally, contrary to EGFR mutations, PD-L1 expression could be a possible predictive biomarker for the therapy of these tumors.

Quantitative Assessment of Preanalytic Variables on Clinical Evaluation of PI3/AKT/mTOR Signaling Activity in Diffuse Glioma.

Biomarker-driven therapeutic clinical trials require the implementation of standardized, evidence-based practices for sample collection. In diffuse glioma, phosphatidylinositol 3 (PI3)-kinase/AKT/mTOR (PI3/AKT/mTOR) signaling is an attractive therapeutic target for which window-of-opportunity clinical trials could facilitate the identification of promising new agents. Yet, the relevant preanalytic variables and optimal tumor sampling methods necessary to measure pathway activity are unknown. To address this, we used a murine model for isocitrate dehydrogenase (IDH)-wildtype glioblastoma (GBM) and human tumor tissue, including IDH-wildtype GBM and IDH-mutant diffuse glioma. First, we determined the impact of delayed time-to-formalin fixation, or cold ischemia time (CIT), on the quantitative assessment of cellular expression of 6 phosphoproteins that are readouts of PI3K/AK/mTOR activity (phosphorylated-proline-rich Akt substrate of 40 kDa (p-PRAS40, T246), -mechanistic target of rapamycin (p-mTOR; S2448); -AKT (p-AKT, S473); -ribosomal protein S6 (p-RPS6, S240/244 and S235/236), and -eukaryotic initiation factor 4E-binding protein 1 (p-4EBP1, T37/46). With CITs ≥ 2 hours, typical of routine clinical handling, all had reduced or altered expression with p-RPS6 (S240/244) exhibiting relatively greater stability. A similar pattern was observed using patient tumor samples from the operating room with p-4EBP1 more sensitive to delayed fixation than p-RPS6 (S240/244). Many clinical trials utilize unstained slides for biomarker evaluation. Thus, we evaluated the impact of slide storage conditions on the detection of p-RPS6 (S240/244), p-4EBP1, and p-AKT. After 5 months, storage at -80°C was required to preserve the expression of p-4EBP1 and p-AKT, whereas p-RPS6 (240/244) expression was not stable regardless of storage temperature. Biomarker heterogeneity impacts optimal tumor sampling. Quantification of p-RPS6 (240/244) expression in multiple regionally distinct human tumor samples from 8 patients revealed significant intratumoral heterogeneity. Thus, the accurate assessment of PI3K/AKT/mTOR signaling in diffuse glioma must overcome intratumoral heterogeneity and multiple preanalytic factors, including time-to-formalin fixation, slide storage conditions, and phosphoprotein of interest.

Proteomics mining of cancer hallmarks on a single-cell resolution.

Dysregulated proteome is an essential contributor in carcinogenesis. Protein fluctuations fuel the progression of malignant transformation, such as uncontrolled proliferation, metastasis, and chemo/radiotherapy resistance, which severely impair therapeutic effectiveness and cause disease recurrence and eventually mortality among cancer patients. Cellular heterogeneity is widely observed in cancer and numerous cell subtypes have been characterized that greatly influence cancer progression. Population-averaged research may not fully reveal the heterogeneity, leading to inaccurate conclusions. Thus, deep mining of the multiplex proteome at the single-cell resolution will provide new insights into cancer biology, to develop prognostic biomarkers and treatments. Considering the recent advances in single-cell proteomics, herein we review several novel technologies with particular focus on single-cell mass spectrometry analysis, and summarize their advantages and practical applications in the diagnosis and treatment for cancer. Technological development in single-cell proteomics will bring a paradigm shift in cancer detection, intervention, and therapy.

Intratumoral Heterogeneity, Chemoresistance and Lymph Node Landing Zone Prognosis in Testicular Tumors Based on Histopathological Characteristics.

BACKGROUND: Existing data on the histopathological correlation of testicular tumors with lymph node prognosis have been poorly explored. We aimed to investigate the relationship of the histopathological properties of testicular tumors with lymph nodes and their involvement with chemoresistance and heterogeneity of testicular tumors. METHODS: Patients with non-seminomatous germ cell tumor (NSGCT) were selected for histopathological correlation of testicular tumor with lymph nodes and its relationship with chemoresistance and heterogeneity. Histopathological and radiological parameters associated with the risk of chemoresistance and tumor progression were measured pre- and post-chemotherapy. Binomial logistic regression and Kaplan-Meier analysis were implemented to determine the predictors of progression and adverse overall patient survival. All categorical variables were analyzed using the Chi-square test, while Pearson's R coefficient determined the correlation. RESULTS: Male patients who were diagnosed with NSGCT from March 2017 to December 2018 at Guwahati Medical College, Guwahati, India, were included in this study. Lymph node groups were predominantly incriminated with the EYST or EYS groups and minimally linked with the pure E and YCS groups. Furthermore, the highest number of lymph node stations was associated with pre-chemotherapy. In salvage chemotherapy in the form of VIP, we found exciting outcomes, as approximately 41% of cases responded positively, especially in the EYS group. CONCLUSION: Our study classifies NSGCT according to the most favorable histopathological grouping and explores the tumoral response in different intrinsic and extrinsic variables. Our analysis can serve as a triumphant histopathological nomogram for a sublime management protocol to deal with the onerous histological pairing in NSGCT.

Clinically relevant molecular hallmarks of PFA ependymomas display intratumoral heterogeneity and correlate with tumor morphology.

Posterior fossa type A (PF-EPN-A, PFA) ependymoma are aggressive tumors that mainly affect children and have a poor prognosis. Histopathology shows significant intratumoral heterogeneity, ranging from loose tissue to often sharply demarcated, extremely cell-dense tumor areas. To determine molecular differences in morphologically different areas and to understand their clinical significance, we analyzed 113 PF-EPN-A samples, including 40 corresponding relapse samples. Cell-dense areas ranged from 0 to 100% of the tumor area and displayed a higher proportion of proliferating tumor cells (p < 0.01). Clinically, cell density was associated with poor progression-free and overall survival (pPFS = 0.0026, pOS < 0.01). Molecularly, tumor areas with low and high cell density showed diverging DNA methylation profiles regarding their similarity to distinct previously discovered PF-EPN-A subtypes in 9/21 cases. Prognostically relevant chromosomal changes at 1q and 6q showed spatial heterogeneity within single tumors and were significantly enriched in cell-dense tumor areas as shown by single-cell RNA (scRNA)-sequencing as well as copy number profiling and fluorescence in situ hybridization (FISH) analyses of different tumor areas. Finally, spatial transcriptomics revealed cell-dense areas of different tumors to be more similar than various different areas of the same tumor. High-density areas distinctly overexpressed genes encoding histone proteins, WNT5A, TGFB1, or IGF2. Relapsing tumors displayed a higher proportion of cell-dense areas (p = 0.036), a change in PF-EPN-A methylation subtypes (13/32 patients), and novel chromosome 1q gains and 6q losses (12/32 cases) compared to corresponding primary tumors. Our data suggest that PF-EPN-A ependymomas habor a previously unrecognized intratumoral heterogeneity with clinical implications, which has to be accounted for when selecting diagnostic material, inter alia, by histological evaluation of the proportion of cell-dense areas.

Molecular classification and intratumoral heterogeneity of gastric adenocarcinoma.

Gastric cancers frequently harbor striking histological complexity and diversity between lesions as well as within single lesions, known as inter- and intratumoral heterogeneity, respectively. The latest World Health Organization Classification of Tumors designated more than 30 histological subtypes for gastric epithelial tumors, assigning 12 subtypes for gastric adenocarcinoma (GAD). Meanwhile, recent advances in genome-wide analyses have provided molecular aspects to the histological classification of GAD, and consequently revealed different molecular traits underlying these histological subtypes. Moreover, accumulating knowledge of comprehensive molecular profiles has led to establishing molecular classifications of GAD, which are often associated with clinical biomarkers for therapeutics and prognosis. However, most of our knowledge of GAD molecular profiles is based on inter-tumoral heterogeneity, and the molecular profiles underlying intratumoral heterogeneity are yet to be determined. In this review, recently established molecular classifications of GAD are introduced in the aspect of pathological diagnosis and are discussed in the context of intratumoral heterogeneity.

Single-cell transcriptome analysis reveals intratumoral heterogeneity in lung adenocarcinoma.

INTRODUCTION: Lung adenocarcinoma (LUAD) is a major health concern worldwide. Single-cell RNA-sequencing (scRNA-seq) provides a valuable platform for exploring the intratumoral heterogeneity in LUAD and holds great potential for facilitating the development and application of personalized therapeutic approaches. METHODS: The TCGA-LUAD (n = 503), GSE68465 (n = 442), GSE72094 (n = 398), and GSE26939 (n = 115) datasets were retrieved for prognostic assessment. Subgroup analysis was performed for the epithelial cells, endothelial cells, immune cells, and fibroblasts, and the transcription factors and tumor-related pathways enriched in each subgroup were analyzed using PROGENy and DoRothEA package. The InferCNV software was used to calculate the copy number variations (CNVs) in tumor cell subgroups with normal epithelial cells as the reference. The association between the annotated cell types and survival was analyzed using the Scissor software. RESULTS: We identified eight major cell types in LUAD, namely epithelial cells, NK cells, T and B cells, endothelial cells, mast cells, myeloid cells, and fibroblasts, of which the epithelial cells and B cells showed a marked increase in the tumor samples. In addition, we also detected an intense signal transduction network from the cancer-associated fibroblasts (CAFs) to malignant cells, mainly involving the DCN/MET, COLA1/DDR1, COL1A1/SDC1, and COL1A2/SDC1 pathways. The tumor differentiation trajectory consisted of state 1 and state 2, which were enriched in HIF1A, and state 4. Furthermore, only a few B cells originated from the normal tissue, suggesting significant recruitment and infiltration of B cells in LUAD. Based on differentially upregulated genes in the cells positively and negatively associated with survival, we established a prognostic model that showed satisfactory predictive performance in three different cohorts. States 3 and 2 of epithelial cells included the majority of cells with KRAS mutation, whereas state 2 showed high frequency of EGFR mutations. CONCLUSION: We analyzed intra-tumor heterogeneity of LUAD at the single-cell level and developed a prognostic index that was highly effective across multiple cohorts.

Small cell lung cancer: Subtypes and therapeutic implications.

Small cell lung cancer (SCLC) is an extremely aggressive neuroendocrine tumor, accounting for approximated 13% of all lung cancer cases. SCLC is characterized by rapid growth and early metastasis. Despite marked improvements in the number and efficacy of targeted, therapeutic options and overall survival rates in SCLC have remained nearly unchanged for almost three decades. The lack of significant progress can be attributed to our poor understanding of the biology of SCLC. Although immune checkpoint inhibitors were recently approved as front-line therapies for SCLC, we still need to better understand the mechanisms responsible for the selective vulnerability of some SCLCs to these inhibitors. Recent work utilizing sequencing data and single cell analyses identified four distinct subsets of SCLC, based on the expression levels of the transcription factors ASCL1, NEUROD1, POU2F3 and YAP1. Each subset was found to have its own distinct biology and therapeutic vulnerabilities. However, these subsets appear to be phenotypically unstable, representing snapshots in the gradual evolution of a tumor that exhibits significant plasticity. Tumor evolution, a product of this plasticity, results in the emergence of significant intratumoral heterogeneity which plays an important role in multiple aspects of SCLC development and progression, including cell survival and proliferation, metastasis and angiogenesis. The recent paradigm shifting discoveries in the biology of SCLC are now beginning to inform the design of new therapeutic strategies for the management of this intractable disease.

Towards deciphering glioblastoma intra-tumoral heterogeneity: The importance of integrating multidimensional models.

Glioblastoma (GBM) is the most common and severe form of brain cancer among adults. Its aggressiveness is largely attributed to its complex and heterogeneous biology that despite maximal surgery and multimodal chemoradiation treatment, inevitably recurs. Traditional large-scale profiling approaches have contributed substantially to the understanding of patient-to-patient inter-tumoral differences in GBM. However, it is now clear that biological differences within an individual (intra-tumoral heterogeneity) are also a prominent factor in treatment resistance and recurrence of GBM and will likely require integration of data from multiple recently developed omics platforms to fully unravel. Here we dissect the growing geospatial model of GBM, which layers intra-tumoral heterogeneity on a GBM stem cell (GSC) precursor, single cell, and spatial level. We discuss potential unique and inter-dependant aspects of the model including potential discordances between observed genotypes and phenotypes in GBM.

Influences of intratumoral heterogeneity on assessment of tumor microenvironment in esophageal squamous cell carcinoma.

The intratumoral heterogeneity (ITH) of the tumor microenvironment (TME) has yet to be addressed in esophageal squamous cell carcinoma (ESCC). Here, we studied the ITH of CD8 and PD-L1 status in ESCC, and examined the potential of the tumor surface for representing the TME. In total, 67 surgically resected clinical Stage II ESCC specimens were analyzed. The CD8-cell density, PD-L1 tumor proportion score (TPS), and combined positive score (CPS) were calculated in three (superficial, middle, and deep) areas of each specimen. ITH was quantified by distance-standardized coefficient variations of the three values. The CD8 and PD-L1 status of each area was dichotomized and tumor-surface capabilities for predicting the entire tumor status were estimated. Variables were compared according to the presence of neoadjuvant chemotherapy (NAC). The ITH, especially PD-L1 heterogeneity, differed markedly among specimens. The concordance rates of CD8 and PD-L1 (CPS and TPS) status among the three different areas were 71.6%, 74.6%, and 73.1%, respectively. The sensitivity and the specificity of the tumor surface for predicting the CD8 status of the whole tumor were high, especially in the NAC- group (both 1.0). The tumor surface also showed high capabilities for representing the whole PD-L1 status, while yielding moderate positive predictive values (0.70). The ITH degrees and predictive capabilities did not differ according to NAC. Taken together, the ITH of CD8 and PD-L1 differed among ESCC specimens, while not being markedly affected by NAC. The use of a biopsy specimen from the tumor surface might be feasible for TME evaluation.

Interactions between driver genes shape the signaling pathway landscape and direct hepatocellular carcinoma therapy.

Hepatocellular carcinoma (HCC) is one of the most lethal malignancies, whose initiation and development are driven by alterations in driver genes. In this study, we identified four driver genes (TP53, PTEN, CTNNB1, and KRAS) that show a high frequency of somatic mutations or copy number variations (CNVs) in patients with HCC. Four different spontaneous HCC mouse models were constructed to screen for changes in various kinase signaling pathways. The sgTrp53 + sgPten tumor upregulated mTOR and noncanonical nuclear factor-κB signaling, which was shown to be strongly inhibited by rapamycin (an mTOR inhibitor) in vitro and in vivo. The JAK-signal transducer and activator of transcription (STAT) signaling was activated in Ctnnb1mut + sgPten tumor, the proliferation of which was strongly inhibited by napabucasin (a STAT3 inhibitor). Additionally, mTOR, cytoskeleton, and AMPK signaling were upregulated while rapamycin and ezrin inhibitors exerted potent antiproliferative effects in sgPten + KrasG12D tumor. We found that JAK-STAT, MAPK, and cytoskeleton signaling were activated in sgTrp53 + KrasG12D tumor and the combination of sorafenib and napabucasin led to the complete inhibition of tumor growth in vivo. In patients with HCC who had the same molecular classification as our mouse models, the downstream signaling pathway landscapes associated with genomic alterations were identical. Our research provides novel targeted therapeutic options for the clinical treatment of HCC, based on the presence of specific genetic alterations within the tumor.

Single-cell transcriptome analysis revealing the intratumoral heterogeneity of ccRCC and validation of MT2A in pathogenesis.

Clear-cell renal cell carcinoma (ccRCC) appears as the most common type of kidney cancer, the carcinogenesis of which has not been fully elucidated. Tumor heterogeneity plays a crucial role in cancer progression, which could be largely deciphered by the implement of scRNA-seq. The bulk and single-cell RNA expression profile is obtained from TCGA and study conducted by Young et al. We utilized UMAP, TSNE, and clustering algorithm Louvain for dimensionality reduction and FindAllMarkers function for determining the DEGs. Monocle2 was utilized to perform pseudo-time series analysis. SCENIC was implemented for transcription factor analysis of each cell subgroup. A series of WB, CFA, CCK-8, and EDU analysis was utilized for the validation of the role of MT2A in ccRCC carcinogenesis. We observed higher infiltration of T/NK and B cells in tumorous tissues, indicating the role of immune cells in ccRCC carcinogenesis. Transcription factor analysis revealed the activation of EOMES and ETS1 in CD8 + T cells, while CAFs were divided into myo-CAFs and i-CAFs, with i-CAFs showing distinct enrichment of ATF3, JUND, JUNB, EGR1, and XBP1. Through cell trajectory analysis, we discerned three distinct stages of cellular evolution, where State2 symbolizes normal renal tubular cells that underwent transitions into State1 and State3 as the CNV score ascended. Functional enrichment examination revealed an amplification of interferon gamma and inflammatory response pathways within tumor cells. The consensus clustering algorithm yielded two molecular subtypes, with cluster 2 being associated with advanced tumor stages and an abundance of infiltrated immune cells. We identified 17 prognostic genes through Cox and LASSO regression models and used them to construct a prognostic model, the efficacy of which was verified in multiple cohorts. Furthermore, we investigated the role of MT2A, one of our hub genes, in ccRCC carcinogenesis, and found it to regulate proliferation and migration of malignant cells. We depicted a detailed single-cell landscape of ccRCC, with special focus on CAFs, endothelial cells, and renal tubular cells. A prognostic model of high stability and accuracy was constructed based on the DEGs. MT2A was found to be actively implicated in ccRCC carcinogenesis, regulating proliferation and migration of the malignant cells.

Unraveling intratumoral complexity in metastatic dermatofibrosarcoma protuberans through single-cell RNA sequencing analysis.

Dermatofibrosarcoma protuberans (DFSP) stands as a rare and locally aggressive soft tissue tumor, characterized by intricated molecular alterations. The imperative to unravel the complexities of intratumor heterogeneity underscores effective clinical management. Herein, we harnessed single-cell RNA sequencing (scRNA-seq) to conduct a comprehensive analysis encompassing samples from primary sites, satellite foci, and lymph node metastases. Rigorous preprocessing of raw scRNA-seq data ensued, and employing t-distributed stochastic neighbor embedding (tSNE) analysis, we unveiled seven major cell populations and fifteen distinct subpopulations. Malignant cell subpopulations were delineated using infercnv for copy number variation calculations. Functional and metabolic variations of diverse malignant cell populations across samples were deciphered utilizing GSVA and the scMetabolism R packages. Additionally, the exploration of differentiation trajectories within diverse fibroblast subpopulations was orchestrated through pseudotime trajectory analyses employing CytoTRACE and Monocle2, and further bolstered by GO analyses to elucidate the functional disparities across distinct differentiation states. In parallel, we segmented the cellular components of the immune microenvironment and verified the presence of SPP1+ macrophage, which constituted the major constituent in lymph node metastases. Remarkably, the CellChat facilitated a comprehensive intercellular communication analysis. This study culminates in an all-encompassing single-cell transcriptome atlas, propounding novel insights into the multifaceted nature of intratumor heterogeneity and fundamental molecular mechanisms propelling metastatic DFSP.