StemSC: a cross-dataset human stemness index for single-cell samples

Epigenetic agents plus anti-PD-1 reprogram the tumor microenvironment and restore antitumor efficacy in Hodgkin lymphoma

ABSTRACT

DNA methyltransferase inhibitor decitabine plus anti-programmed cell death 1 (DP) therapy was effective in relapsed/refractory classic Hodgkin lymphoma (cHL). However, a subset of patients experienced primary resistance or relapse/progression after DP therapy. In this study, we evaluated the efficacy and safety of a triplet regimen consisting of the histone deacetylase inhibitor chidamide, decitabine, and anti-PD-1 camrelizumab (CDP) in 52 patients who previously received DP therapy. CDP treatment was well tolerated and resulted in an objective response rate of 94% (95% confidence interval [CI], 84-99), with 50% (95% CI, 36-64) of patients achieving complete response (CR). Notably, all patients who were recalcitrant to previous DP treatment exhibited therapeutic responses after CDP therapy, although their CR rate was lower than patients responsive to prior DP. Overall, the median progression-free survival was 29.4 months. Through single-cell RNA sequencing of pretreatment and on-treatment cHL tumor biopsy samples, we observed the heterogeneity of rare malignant Hodgkin Reed/Sternberg (HRS)-like cells. The classical CD30+ HRS-like cells interacted with abundant immunosuppressive IL21+CD4+ T helper cells, forming a positive feedback loop that supported their survival. While the CD30- HRS-like cell population showed potential resistance to anti-PD-1 immunotherapy. CDP treatment promoted the activation of diverse tumor-reactive CD8+ T cells and suppressed the proliferation of IL21+CD4+ T cells by inhibiting STAT1/3 signaling, thereby alleviating their immunosuppressive effects. These findings provide insights into the cHL microenvironment that contributes to anti-PD-1 resistance and highlight the therapeutic effectiveness of dual epi-immunotherapy in overcoming immunotherapy resistance. This trial was registered at www.clinicaltrials.gov as #NCT04233294.

Cancer Stemness Online: A Resource for Investigating Cancer Stemness and Associations with Immune Response

Cancer progression involves the gradual loss of a differentiated phenotype and the acquisition of progenitor and stem cell-like features, which are potential culprits of immunotherapy resistance. Although the state-of-the-art predictive computational methods have facilitated the prediction of cancer stemness, there remains a lack of efficient resources to accommodate various usage requirements. Here, we present the Cancer Stemness Online, an integrated resource for efficiently scoring cancer stemness potential at both bulk and single-cell levels. This resource integrates eight robust predictive algorithms as well as 27 signature gene sets associated with cancer stemness for predicting stemness scores. Downstream analyses were performed from five distinct aspects: identifying the signature genes of cancer stemness; exploring the associations with cancer hallmarks and cellular states; exploring the associations with immune response and the communications with immune cells; investigating the contributions to patient survival; and performing a robustness analysis of cancer stemness among different methods. Moreover, the pre-calculated cancer stemness atlas for more than 40 cancer types can be accessed by users. Both the tables and diverse visualizations of the analytical results are available for download. Together, Cancer Stemness Online is a powerful resource for scoring cancer stemness and expanding downstream functional interpretation, including immune response and cancer hallmarks. Cancer Stemness Online is freely accessible at http://bio-bigdata.hrbmu.edu.cn/CancerStemnessOnline.

Targeting axonal guidance dependencies in glioblastoma with ROBO1 CAR T cells

Resistance to genotoxic therapies and tumor recurrence are hallmarks of glioblastoma (GBM), an aggressive brain tumor. In this study, we investigated functional drivers of post-treatment recurrent GBM through integrative genomic analyses, genome-wide genetic perturbation screens in patient-derived GBM models and independent lines of validation. Specific genetic dependencies were found consistent across recurrent tumor models, accompanied by increased mutational burden and differential transcript and protein expression compared to its primary GBM predecessor. Our observations suggest a multi-layered genetic response to drive tumor recurrence and implicate PTP4A2 (protein tyrosine phosphatase 4A2) as a modulator of self-renewal, proliferation and tumorigenicity in recurrent GBM. Genetic perturbation or small-molecule inhibition of PTP4A2 acts through a dephosphorylation axis with roundabout guidance receptor 1 (ROBO1) and its downstream molecular players, exploiting a functional dependency on ROBO signaling. Because a pan-PTP4A inhibitor was limited by poor penetrance across the blood-brain barrier in vivo, we engineered a second-generation chimeric antigen receptor (CAR) T cell therapy against ROBO1, a cell surface receptor enriched across recurrent GBM specimens. A single dose of ROBO1-targeted CAR T cells doubled median survival in cell-line-derived xenograft (CDX) models of recurrent GBM. Moreover, in CDX models of adult lung-to-brain metastases and pediatric relapsed medulloblastoma, ROBO1 CAR T cells eradicated tumors in 50-100% of mice. Our study identifies a promising multi-targetable PTP4A-ROBO1 signaling axis that drives tumorigenicity in recurrent GBM, with potential in other malignant brain tumors.

Aberrant activation of TGF-β/ROCK1 enhances stemness during prostatic stromal hyperplasia

Benign prostatic hyperplasia (BPH) is a multifactorial disease in which abnormal growth factor activation and embryonic reawakening are considered important factors. Here we demonstrated that the aberrant activation of transforming growth factor β (TGF-β)/Rho kinase 1 (ROCK1) increased the stemness of BPH tissue by recruiting mesenchymal stem cells (MSCs), indicating the important role of embryonic reawakening in BPH. When TGF-β/ROCK1 is abnormally activated, MSCs are recruited and differentiate into fibroblasts/myofibroblasts, leading to prostate stromal hyperplasia. Further research showed that inhibition of ROCK1 activation suppressed MSC migration and their potential for stromal differentiation. Collectively, our findings suggest that abnormal activation of TGF-β/ROCK1 regulates stem cell lineage specificity, and the small molecule inhibitor GSK269962A could target ROCK1 and may be a potential treatment for BPH.

Single-cell multi-omics analysis of lineage development and spatial organization in the human fetal cerebellum

Human cerebellum encompasses numerous neurons, exhibiting a distinct developmental paradigm from cerebrum. Here we conducted scRNA-seq, scATAC-seq and spatial transcriptomic analyses of fetal samples from gestational week (GW) 13 to 18 to explore the emergence of cellular diversity and developmental programs in the developing human cerebellum. We identified transitory granule cell progenitors that are conserved across species. Special patterns in both granule cells and Purkinje cells were dissected multidimensionally. Species-specific gene expression patterns of cerebellar lobes were characterized and we found that PARM1 exhibited inconsistent distribution in human and mouse granule cells. A novel cluster of potential neuroepithelium at the rhombic lip was identified. We also resolved various subtypes of Purkinje cells and unipolar brush cells and revealed gene regulatory networks controlling their diversification. Therefore, our study offers a valuable multi-omics landscape of human fetal cerebellum and advances our understanding of development and spatial organization of human cerebellum.

Quantitative Modeling of Stemness in Single-Cell RNA Sequencing Data: A Nonlinear One-Class Support Vector Machine Method

Intratumoral heterogeneity and the presence of cancer stem cells are challenging issues in cancer therapy. An appropriate quantification of the stemness of individual cells for assessing the potential for self-renewal and differentiation from the cell of origin can define a measurement for quantifying different cell states, which is important in understanding the dynamics of cancer evolution, and might further provide possible targeted therapies aimed at tumor stem cells. Nevertheless, it is usually difficult to quantify the stemness of a cell based on molecular information associated with the cell. In this study, we proposed a stemness definition method with one-class Hadamard kernel support vector machine (OCHSVM) based on single-cell RNA sequencing (scRNA-seq) data. Applications of the proposed OCHSVM stemness are assessed by various data sets, including preimplantation embryo cells, induced pluripotent stem cells, or tumor cells. We further compared the OCHSVM model with state-of-the-art methods CytoTRACE, one-class logistic regression, or one-class SVM methods with different kernels. The computational results demonstrate that the OCHSVM method is more suitable for stemness identification using scRNA-seq data.

Prostate cancer as a dedifferentiated organ: androgen receptor, cancer stem cells, and cancer stemness

Cancer progression is characterized and driven by gradual loss of a differentiated phenotype and gain of stem cell-like features. In prostate cancer (PCa), androgen receptor (AR) signaling is important for cancer growth, progression, and emergence of therapy resistance. Targeting the AR signaling axis has been, over the decades, the mainstay of PCa therapy. However, AR signaling at the transcription level is reduced in high-grade cancer relative to low-grade PCa and loss of AR expression promotes a stem cell-like phenotype, suggesting that emergence of resistance to AR-targeted therapy may be associated with loss of AR signaling and gain of stemness. In the present mini-review, we first discuss PCa from the perspective of an abnormal organ with increasingly deregulated differentiation, and discuss the role of AR signaling during PCa progression. We then focus on the relationship between prostate cancer stem cells (PCSCs) and AR signaling. We further elaborate on the current methods of using transcriptome-based stemness-enriched signature to evaluate the degree of oncogenic dedifferentiation (cancer stemness) in pan-cancer datasets, and present the clinical significance of scoring transcriptome-based stemness across the spectrum of PCa development. Our discussions highlight the importance to evaluate the dynamic changes in both stem cell-like features (stemness score) and AR signaling activity across the PCa spectrum.