Opposing immune and genetic mechanisms shape oncogenic programs in synovial sarcoma

Pan-cancer mapping of single CD8+ T cell profiles reveals a TCF1:CXCR6 axis regulating CD28 co-stimulation and anti-tumor immunity

CD8+ T cells must persist and function in diverse tumor microenvironments to exert their effects. Thus, understanding common underlying expression programs could better inform the next generation of immunotherapies. We apply a generalizable matrix factorization algorithm that recovers both shared and context-specific expression programs from diverse datasets to a single-cell RNA sequencing (scRNA-seq) compendium of 33,161 CD8+ T cells from 132 patients with seven human cancers. Our meta-single-cell analyses uncover a pan-cancer T cell dysfunction program that predicts clinical non-response to checkpoint blockade in melanoma and highlights CXCR6 as a pan-cancer marker of chronically activated T cells. Cxcr6 is trans-activated by AP-1 and repressed by TCF1. Using mouse models, we show that Cxcr6 deletion in CD8+ T cells increases apoptosis of PD1+TIM3+ cells, dampens CD28 signaling, and compromises tumor growth control. Our study uncovers a TCF1:CXCR6 axis that counterbalances PD1-mediated suppression of CD8+ cell responses and is essential for effective anti-tumor immunity.

Single-cell multiomics profiling reveals heterogeneous transcriptional programs and microenvironment in DSRCTs

Desmoplastic small round cell tumor (DSRCT) is a rare, aggressive sarcoma driven by the EWSR1::WT1 chimeric transcription factor. Despite this unique oncogenic driver, DSRCT displays a polyphenotypic differentiation of unknown causality. Using single-cell multi-omics on 12 samples from five patients, we find that DSRCT tumor cells cluster into consistent subpopulations with partially overlapping lineage- and metabolism-related transcriptional programs. In vitro modeling shows that high EWSR1::WT1 DNA-binding activity associates with most lineage-related states, in contrast to glycolytic and profibrotic states. Single-cell chromatin accessibility analysis suggests that EWSR1::WT1 binding site variability may drive distinct lineage-related transcriptional programs, supporting some level of cell-intrinsic plasticity. Spatial transcriptomics reveals that glycolytic and profibrotic states specifically localize within hypoxic niches at the periphery of tumor cell islets, suggesting an additional role of tumor cell-extrinsic microenvironmental cues. We finally identify a single-cell transcriptomics-derived epithelial signature associated with improved patient survival, highlighting the clinical relevance of our findings.

Comprehensive single cell transcriptomics analysis of murine osteosarcoma uncovers Skp2 function in metastasis, genomic instability and immune activation and reveals additional target pathways

Osteosarcoma (OS) is the most common primary pediatric bone malignancy. One promising new therapeutic target is SKP2, encoding a substrate recognition factor of the SCF E3 ubiquitin ligase responsible for ubiquitination and proteasome degradation of substrate p27, thus driving cellular proliferation. We have shown previously that knockout of Skp2 in an immunocompetent transgenic mouse model of OS improved survival, drove apoptosis, and induced tumor inflammation. Here, we applied single-cell RNA-sequencing (scRNA-seq) to study primary OS tumors derived from Osx-Cre driven conditional knockout of Rb1 and Trp53. We showed that murine OS models recapitulate the tumor heterogeneity and microenvironment complexity observed in patient tumors. We further compared this model with OS models with functional disruption of Skp2: one with Skp2 knockout and the other with the Skp2-p27 interaction disrupted (resulting in p27 overexpression). We found reduction of T cell exhaustion and upregulation of interferon activation, along with evidence of replicative and endoplasmic reticulum-related stress in the Skp2 disruption models, and showed that interferon induction was correlated with improved survival in OS patients. Additionally, our scRNA-seq analysis uncovered decreased activities of metastasis-related gene signatures in the Skp2-disrupted OS, which we validated by observation of a strong reduction in lung metastasis in the Skp2 knockout mice. Finally, we report several potential mechanisms of escape from targeting Skp2 in OS, including upregulation of Myc targets, DNA copy number amplification and overexpression of alternative E3 ligase genes, and potential alternative lineage activation. These mechanistic insights into OS tumor biology and Skp2 function suggest novel targets for new, synergistic therapies, while the data and our comprehensive analysis may serve as a public resource for further big data-driven OS research.

Biological and therapeutic insights from animal modeling of fusion-driven pediatric soft tissue sarcomas

Survival for children with cancer has primarily improved over the past decades due to refinements in surgery, radiation and chemotherapy. Although these general therapies are sometimes curative, the cancer often recurs, resulting in poor outcomes for patients. Fusion-driven pediatric soft tissue sarcomas are genetically defined by chromosomal translocations that create a chimeric oncogene. This distinctive, almost 'monogenic', genetic feature supports the generation of animal models to study the respective diseases in vivo. This Review focuses on a subset of fusion-driven pediatric soft tissue sarcomas that have transgenic animal tumor models, which includes fusion-positive and infantile rhabdomyosarcoma, synovial sarcoma, undifferentiated small round cell sarcoma, alveolar soft part sarcoma and clear cell sarcoma. Studies using the animal models of these sarcomas have highlighted that pediatric cancers require a specific cellular state or developmental stage to drive tumorigenesis, as the fusion oncogenes cause different outcomes depending on their lineage and timing of expression. Therefore, understanding these context-specific activities could identify targetable activities and mechanisms critical for tumorigenesis. Broadly, these cancers show dependencies on chromatin regulators to support oncogenic gene expression and co-opting of developmental pathways. Comparative analyses across lineages and tumor models will further provide biological and therapeutic insights to improve outcomes for these children.

Synovial Sarcoma Chromatin Dynamics Reveal a Continuum in SS18:SSX Reprograming

Synovial sarcoma (SyS) is an aggressive soft-tissue malignancy characterized by a pathognomonic chromosomal translocation leading to the formation of the SS18::SSX fusion oncoprotein. SS18::SSX associates with mammalian BAF complexes suggesting deregulation of chromatin architecture as the oncogenic driver in this tumour type. To examine the epigenomic state of SyS we performed comprehensive multi-omics analysis on 52 primary pre-treatment human SyS tumours. Our analysis revealed a continuum of epigenomic states across the cohort at fusion target genes independent of rare somatic genetic lesions. We identify cell-of-origin signatures defined by enhancer states and reveal unexpected relationships between H2AK119Ub1 and active marks. The number of bivalent promoters, dually marked by the repressive H3K27me3 and activating H3K4me3 marks, has strong prognostic value and outperforms tumor grade in predicting patient outcome. Finally, we identify SyS defining epigenomic features including H3K4me3 expansion associated with striking promoter DNA hypomethylation in which SyS displays the lowest mean methylation level of any sarcoma subtype. We explore these distinctive features as potential vulnerabilities in SyS and identify H3K4me3 inhibition as a promising therapeutic strategy.

Sarcoma microenvironment cell states and ecosystems are associated with prognosis and predict response to immunotherapy

Characterization of the diverse malignant and stromal cell states that make up soft tissue sarcomas and their correlation with patient outcomes has proven difficult using fixed clinical specimens. Here, we employed EcoTyper, a machine-learning framework, to identify the fundamental cell states and cellular ecosystems that make up sarcomas on a large scale using bulk transcriptomes with clinical annotations. We identified and validated 23 sarcoma-specific, transcriptionally defined cell states, many of which were highly prognostic of patient outcomes across independent datasets. We discovered three conserved cellular communities or ecotypes associated with underlying genomic alterations and distinct clinical outcomes. We show that one ecotype defined by tumor-associated macrophages and epithelial-like malignant cells predicts response to immune-checkpoint inhibition but not chemotherapy and validate our findings in an independent cohort. Our results may enable identification of patients with soft tissue sarcomas who could benefit from immunotherapy and help develop new therapeutic strategies.

Identifying cancer subtypes based on embryonic and hematopoietic stem cell signatures in pan-cancer

PURPOSE

Cancer cells with stem cell-like properties may contribute to cancer development and therapy resistance. The advancement of multi-omics technology has sparked interest in exploring cancer stemness from a multi-omics perspective. However, there is a limited number of studies that have attempted to subtype cancer by combining different types of stem cell signatures.

METHODS

In this study, 10,323 cancer specimens from 33 TCGA cancer types were clustered based on the enrichment scores of six stemness gene sets, representing two types of stem cell backgrounds: embryonic stem cells (ESCs) and hematopoietic stem cells (HSCs).

RESULTS

We identified four subtypes of pan-cancer, termed StC1, StC2, StC3 and StC4, which displayed distinct molecular and clinical features, including stemness, genome integrity, intratumor heterogeneity, methylation levels, tumor microenvironment, tumor progression, responses to chemotherapy and immunotherapy, and survival prognosis. Importantly, this subtyping method for pan-cancer is reproducible at the protein level.

CONCLUSION

Our findings indicate that the ESC signature is an adverse prognostic factor in cancer, while the HSC signature and ratio of HSC/ESC signatures are positive prognostic factors. The subtyping of cancer based on ESC and HSC signatures may provide insights into cancer biology and clinical implications of cancer.

CFLAR: A novel diagnostic and prognostic biomarker in soft tissue sarcoma, which positively modulates the immune response in the tumor microenvironment

Anoikis is highly associated with tumor cell apoptosis and tumor prognosis; however, the specific role of anoikis-related genes (ARGs) in soft tissue sarcoma (STS) remains to be fully elucidated. The present study aimed to use a variety of bioinformatics methods to determine differentially expressed anoikis-related genes in STS and healthy tissues. Subsequently, three machine learning algorithms, Least Absolute Shrinkage and Selection Operator, Support Vector Machine and Random Forest, were used to screen genes with the highest importance score. The results of the bioinformatics analyses demonstrated that CASP8 and FADD-like apoptosis regulator (CFLAR) exhibited the highest importance score. Subsequently, the diagnostic and prognostic value of CFLAR in STS development was determined using multiple public and in-house cohorts. The results of the present study demonstrated that CFLAR may be considered a diagnostic and prognostic marker of STS, which acts as an independent prognostic factor of STS development. The present study also aimed to explore the potential role of CFLAR in the STS tumor microenvironment, and the results demonstrated that CFLAR significantly enhanced the immune response of STS, and exerted a positive effect on the infiltration of CD8+ T cells and M1 macrophages in the STS immune microenvironment. Notably, the aforementioned results were verified using multiplex immunofluorescence analysis. Collectively, the results of the present study demonstrated that CFLAR may act as a novel diagnostic and prognostic marker for STS, and may positively regulate the immune response of STS. Thus, the present study provided a novel theoretical basis for the use of CFLAR in STS diagnosis, in predicting clinical outcomes and in tailoring individualized treatment options.

Opportunity in Complexity: Harnessing Molecular Biomarkers and Liquid Biopsies for Personalized Sarcoma Care

Due to their rarity and complexity, sarcomas represent a substantial therapeutic challenge. However, the incredible diversity within and across sarcoma subtypes presents an opportunity for personalized care to maximize efficacy and limit toxicity. A deeper understanding of the molecular alterations that drive sarcoma development and treatment response has paved the way for molecular biomarkers to shape sarcoma treatment. Genetic, transcriptomic, and protein biomarkers have become critical tools for diagnosis, prognostication, and treatment selection in patients with sarcomas. In the future, emerging biomarkers like circulating tumor DNA analysis offer the potential to improve early detection, monitoring response to treatment, and identifying mechanisms of resistance to personalize sarcoma treatment. Here, we review the current state of molecular biomarkers for sarcomas and highlight opportunities and challenges for the implementation of new technologies in the future.

BCG as an Innovative Option for HCC Treatment: Repurposing and Mechanistic Insights

This study investigates Bacillus Calmette-Guérin (BCG) as a potential treatment for hepatocellular carcinoma (HCC), a condition often associated with unfavorable treatment outcomes. Exploiting BCG's recognized immune-boosting properties, preclinical trials are conducted using HCC mice, with a single subcutaneous dose of BCG administered post-tumor formation. Results indicate that BCG treatment effectively diminishes tumor burden and extends survival in both male and female HCC mice. Positive influences on hepatic fibrosis and metabolism are observed, leading to a reduction in lipid levels. Spatial analysis underscores BCG's tumor-specific effects, inducing the enrichment of metabolic pathways and inhibiting various cancer-related pathways. Furthermore, BCG promotes immune cell infiltration, including CD4+, CD8+ T cells, and M1 macrophages, in both v-akt murine thymoma viral oncogene homolog 1(AKT)/neutoblastoma RAS viral oncogene homolog (RAS) and β-catenin positive HCC models. Interestingly, blocking T cells, trained immunity, and Interferon-γ (IFN-γ) function reverses BCG's anti-HCC effects. In conclusion, BCG emerges as a promising treatment option for HCC, characterized by a favorable safety profile and efficacy in inhibiting fibrosis, improving metabolism, and engaging both trained immunity and T cells in therapeutic mechanisms.

A cellular and spatial atlas of TP53 -associated tissue remodeling in lung adenocarcinoma

TP53 is the most frequently mutated gene across many cancers and is associated with shorter survival in lung adenocarcinoma (LUAD). To define how TP53 mutations affect the LUAD tumor microenvironment (TME), we constructed a multi-omic cellular and spatial tumor atlas of 23 treatment-naïve human lung tumors. We found that TP53 -mutant ( TP53 mut ) malignant cells lose alveolar identity and upregulate highly proliferative and entropic gene expression programs consistently across resectable LUAD patient tumors, genetically engineered mouse models, and cell lines harboring a wide spectrum of TP53 mutations. We further identified a multicellular tumor niche composed of SPP1 + macrophages and collagen-expressing fibroblasts that coincides with hypoxic, pro-metastatic expression programs in TP53 mut tumors. Spatially correlated angiostatic and immune checkpoint interactions, including CD274 - PDCD1 and PVR - TIGIT , are also enriched in TP53 mut LUAD tumors, which may influence response to checkpoint blockade therapy. Our methodology can be further applied to investigate mutation-specific TME changes in other cancers.

Whole transcriptome profiling of placental pathobiology in SARS-CoV-2 pregnancies identifies placental dysfunction signatures

Objectives

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) virus infection in pregnancy is associated with higher incidence of placental dysfunction, referred to by a few studies as a 'preeclampsia-like syndrome'. However, the mechanisms underpinning SARS-CoV-2-induced placental malfunction are still unclear. Here, we investigated whether the transcriptional architecture of the placenta is altered in response to SARS-CoV-2 infection.

Methods

We utilised whole-transcriptome, digital spatial profiling, to examine gene expression patterns in placental tissues from participants who contracted SARS-CoV-2 in the third trimester of their pregnancy (n = 7) and those collected prior to the start of the coronavirus disease 2019 (COVID-19) pandemic (n = 9).

Results

Through comprehensive spatial transcriptomic analyses of the trophoblast and villous core stromal cell subpopulations in the placenta, we identified SARS-CoV-2 to promote signatures associated with hypoxia and placental dysfunction. Notably, genes associated with vasodilation (NOS3), oxidative stress (GDF15, CRH) and preeclampsia (FLT1, EGFR, KISS1, PAPPA2) were enriched with SARS-CoV-2. Pathways related to increased nutrient uptake, vascular tension, hypertension and inflammation were also enriched in SARS-CoV-2 samples compared to uninfected controls.

Conclusions

Our findings demonstrate the utility of spatially resolved transcriptomic analysis in defining the underlying pathogenic mechanisms of SARS-CoV-2 in pregnancy, particularly its role in placental dysfunction. Furthermore, this study highlights the significance of digital spatial profiling in mapping the intricate crosstalk between trophoblasts and villous core stromal cells, thus shedding light on pathways associated with placental dysfunction in pregnancies with SARS-CoV-2 infection.

Challenges and opportunities in rare cancer research in China

Cancer is one of the major public health challenges in China. Rare cancers collectively account for a considerable proportion of all malignancies. The lack of awareness of rare cancers among healthcare professionals and the general public, the typically complex and delayed diagnosis, and limited access to clinical trials are key challenges. Recent years have witnessed an increase in funding for research related to rare cancers in China. In this review, we provide a comprehensive overview of rare cancers and summarize the status of research on rare cancers in China and overseas, including the trends of funding and publications. We also highlight the challenges and perspectives regarding rare cancers in China.

Stroma AReactive Invasion Front Areas (SARIFA) proves prognostic relevance in gastric carcinoma and is based on a tumor-adipocyte interaction indicating an altered immune response

BACKGROUND

Recently, we presented Stroma AReactive Invasion Front Areas (SARIFA) as a new histomorphologic negative prognostic biomarker in gastric cancer. It is defined as direct contact between tumor cells and fat cells. The aim of this study was to further elucidate the underlying genomic, transcriptional, and immunological mechanisms of the SARIFA phenomenon.

METHODS

To address these questions, SARIFA was classified on H&E-stained tissue sections of three cohorts: an external cohort (n = 489, prognostic validation), the TCGA-STAD cohort (n = 194, genomic and transcriptomic analysis), and a local cohort (n = 60, digital spatial profiling (whole transcriptome) and double RNA in situ hybridization/immunostaining of cytokines).

RESULTS

SARIFA status proved to be an independent negative prognostic factor for overall survival in an external cohort of gastric carcinomas. In TCGA-STAD cohort, SARIFA is not driven by distinct genomic alterations, whereas the gene expression analyses showed an upregulation of FABP4 in SARIFA-positive tumors. In addition, the transcriptional regulations of white adipocyte differentiation, triglyceride metabolism, and catabolism were upregulated in pathway analyses. In the DSP analysis of SARIFA-positive tumors, FABP4 and the transcriptional regulation of white adipocyte differentiation were upregulated in macrophages. Additionally, a significantly lower expression of the cytokines IL6 and TNFα was observed at the invasion front.

CONCLUSIONS

SARIFA proves to be a strong negative prognostic biomarker in advanced gastric cancer, implicating an interaction of tumor cells with tumor-promoting adipocytes with crucial changes in tumor cell metabolism. SARIFA is not driven by tumor genetics but is very likely driven by an altered immune response as a causative mechanism.

Mapping the transcriptome: Realizing the full potential of spatial data analysis

RNA sequencing in situ allows for whole-transcriptome characterization at high resolution, while retaining spatial information. These data present an analytical challenge for bioinformatics-how to leverage spatial information effectively? Properties of data with a spatial dimension require special handling, which necessitate a different set of statistical and inferential considerations when compared to non-spatial data. The geographical sciences primarily use spatial data and have developed methods to analye them. Here we discuss the challenges associated with spatial analysis and examine how we can take advantage of practice from the geographical sciences to realize the full potential of spatial information in transcriptomic datasets.

Personalized tumor combination therapy optimization using the single-cell transcriptome

BACKGROUND

The precise characterization of individual tumors and immune microenvironments using transcriptome sequencing has provided a great opportunity for successful personalized cancer treatment. However, the cancer treatment response is often characterized by in vitro assays or bulk transcriptomes that neglect the heterogeneity of malignant tumors in vivo and the immune microenvironment, motivating the need to use single-cell transcriptomes for personalized cancer treatment.

METHODS

Here, we present comboSC, a computational proof-of-concept study to explore the feasibility of personalized cancer combination therapy optimization using single-cell transcriptomes. ComboSC provides a workable solution to stratify individual patient samples based on quantitative evaluation of their personalized immune microenvironment with single-cell RNA sequencing and maximize the translational potential of in vitro cellular response to unify the identification of synergistic drug/small molecule combinations or small molecules that can be paired with immune checkpoint inhibitors to boost immunotherapy from a large collection of small molecules and drugs, and finally prioritize them for personalized clinical use based on bipartition graph optimization.

RESULTS

We apply comboSC to publicly available 119 single-cell transcriptome data from a comprehensive set of 119 tumor samples from 15 cancer types and validate the predicted drug combination with literature evidence, mining clinical trial data, perturbation of patient-derived cell line data, and finally in-vivo samples.

CONCLUSIONS

Overall, comboSC provides a feasible and one-stop computational prototype and a proof-of-concept study to predict potential drug combinations for further experimental validation and clinical usage using the single-cell transcriptome, which will facilitate and accelerate personalized tumor treatment by reducing screening time from a large drug combination space and saving valuable treatment time for individual patients. A user-friendly web server of comboSC for both clinical and research users is available at www.combosc.top . The source code is also available on GitHub at https://github.com/bm2-lab/comboSC .

Inflammation in the tumor-adjacent lung as a predictor of clinical outcome in lung adenocarcinoma

Approximately 30% of early-stage lung adenocarcinoma patients present with disease progression after successful surgical resection. Despite efforts of mapping the genetic landscape, there has been limited success in discovering predictive biomarkers of disease outcomes. Here we performed a systematic multi-omic assessment of 143 tumors and matched tumor-adjacent, histologically-normal lung tissue with long-term patient follow-up. Through histologic, mutational, and transcriptomic profiling of tumor and adjacent-normal tissue, we identified an inflammatory gene signature in tumor-adjacent tissue as the strongest clinical predictor of disease progression. Single-cell transcriptomic analysis demonstrated the progression-associated inflammatory signature was expressed in both immune and non-immune cells, and cell type-specific profiling in monocytes further improved outcome predictions. Additional analyses of tumor-adjacent transcriptomic data from The Cancer Genome Atlas validated the association of the inflammatory signature with worse outcomes across cancers. Collectively, our study suggests that molecular profiling of tumor-adjacent tissue can identify patients at high risk for disease progression.

Aberrant gene activation in synovial sarcoma relies on SSX specificity and increased PRC1.1 stability

The SS18-SSX fusion drives oncogenic transformation in synovial sarcoma by bridging SS18, a member of the mSWI/SNF (BAF) complex, to Polycomb repressive complex 1 (PRC1) target genes. Here we show that the ability of SS18-SSX to occupy H2AK119ub1-rich regions is an intrinsic property of its SSX C terminus, which can be exploited by fusion to transcriptional regulators beyond SS18. Accordingly, SS18-SSX recruitment occurs in a manner that is independent of the core components and catalytic activity of BAF. Alternative SSX fusions are also recruited to H2AK119ub1-rich chromatin and reproduce the expression signatures of SS18-SSX by engaging with transcriptional activators. Variant Polycomb repressive complex 1.1 (PRC1.1) acts as the main depositor of H2AK119ub1 and is therefore required for SS18-SSX occupancy. Importantly, the SSX C terminus not only depends on H2AK119ub1 for localization, but also further increases it by promoting PRC1.1 complex stability. Consequently, high H2AK119ub1 levels are a feature of murine and human synovial sarcomas. These results uncover a critical role for SSX-C in mediating gene deregulation in synovial sarcoma by providing specificity to chromatin and further enabling oncofusion binding by enhancing PRC1.1 stability and H2AK119ub1 deposition.

VISTA Expression on Cancer-Associated Endothelium Selectively Prevents T-cell Extravasation

Cancers evade T-cell immunity by several mechanisms such as secretion of anti-inflammatory cytokines, down regulation of antigen presentation machinery, upregulation of immune checkpoint molecules, and exclusion of T cells from tumor tissues. The distribution and function of immune checkpoint molecules on tumor cells and tumor-infiltrating leukocytes is well established, but less is known about their impact on intratumoral endothelial cells. Here, we demonstrated that V-domain Ig suppressor of T-cell activation (VISTA), a PD-L1 homolog, was highly expressed on endothelial cells in synovial sarcoma, subsets of different carcinomas, and immune-privileged tissues. We created an ex vivo model of the human vasculature and demonstrated that expression of VISTA on endothelial cells selectively prevented T-cell transmigration over endothelial layers under physiologic flow conditions, whereas it does not affect migration of other immune cell types. Furthermore, endothelial VISTA correlated with reduced infiltration of T cells and poor prognosis in metastatic synovial sarcoma. In endothelial cells, we detected VISTA on the plasma membrane and in recycling endosomes, and its expression was upregulated by cancer cell-secreted factors in a VEGF-A-dependent manner. Our study reveals that endothelial VISTA is upregulated by cancer-secreted factors and that it regulates T-cell accessibility to cancer and healthy tissues. This newly identified mechanism should be considered when using immunotherapeutic approaches aimed at unleashing T cell-mediated cancer immunity.

Synovial sarcoma in the prevertebral space can mimic malignant neurogenic neoplasm: Case report and literature review

Synovial sarcoma, a rare malignant neoplasm with a poor prognosis, accounts for approximately 5%-10% of all primary soft-tissue malignancies worldwide. Typically affecting adolescents and young adults, it primarily manifests near the joints of the lower extremities. This study aimed to demonstrate that this tumor can also affect the prevertebral space. A 32-year-old male patient presented at our outpatient clinic with a 2-month history of upper limb numbness and a 1-month complaint of palpable neck mass. Imaging studies revealed a bulky, lobulated, and heterogeneous mass exhibiting heterogeneous enhancement. Furthermore, the mass caused expansion of the neuroforamen in the neck, initially suggesting a diagnosis of malignant schwannoma. However, a histopathologic examination suggested synovial sarcoma. The article provided a comprehensive review of the clinical, pathological, and radiological features of this condition. Additionally, it explored current treatment options and prognoses by referencing relevant literature.

Treatment at Relapse for Synovial Sarcoma of Children, Adolescents and Young Adults: From the State of Art to Future Clinical Perspectives

While the overall prognosis is generally quite satisfactory in children, adolescents and young adults with localised synovial sarcoma at first diagnosis, the outcome remains poor for patients after relapse. Conversely to the front-line standardised treatment options, patients with relapse generally have an individualised approach and to date, there is still a lack of consensus regarding standard treatment approaches. Studies on relapsed synovial sarcoma were able to identify some prognostic variables that influence post-relapse survival, in order to plan risk-adapted salvage protocols. Treatment proposals must consider previous first-line treatments, potential toxicities, and the possibility of achieving an adequate local treatment by new surgery and/or re-irradiation. Effective second-line drug therapies are urgently needed. Notably, experimental treatments such as adoptive engineered TCR-T cell immunotherapy seem promising in adults and are currently under validation also in paediatric patients.

Innovative Breakthroughs for the Treatment of Advanced and Metastatic Synovial Sarcoma

Synovial sarcoma (SyS) is a rare aggressive soft tissue sarcoma carrying the chromosomal translocation t(X;18), encoding the fusion transcript SS18::SSX. The fusion oncoprotein interacts with both BAF enhancer complexes and polycomb repressor complexes, resulting in genome-wide epigenetic perturbations and a unique altered genetic signature. Over 80% of the patients are initially diagnosed with localized disease and have a 5-year survival rate of 70-80%, but metastatic relapse occurs in 50% of the cases. Advanced, unresectable, or metastatic disease has a 5-year survival rate below 10%, representing a critical issue. This review summarizes the molecular mechanisms behind SyS and illustrates current treatments in front line, second line, and beyond settings. We analyze the use of immune check point inhibitors (ICI) in SyS that do not behave as an ICI-sensitive tumor, claiming the need for predictive genetic signatures and tumor immune microenvironment biomarkers. We highlight the clinical translation of innovative technologies, such as proteolysis targeting chimera (PROTAC) protein degraders or adoptive transfer of engineered immune cells. Adoptive cell transfer of engineered T-cell receptor cells targeting selected cancer/testis antigens has shown promising results against metastatic SyS in early clinical trials and further improvements are awaited from refinements involving immune cell engineering and tumor immune microenvironment enhancement.

Integration analysis of senescence-related genes to predict prognosis and immunotherapy response in soft-tissue sarcoma: evidence based on machine learning and experiments

Background: Soft tissue sarcoma (STS) is the malignancy that exhibits remarkable histologic diversity. The diagnosis and treatment of STS is currently challenging, resulting in a high lethality. Chronic inflammation has also been identified as a key characteristic of tumors, including sarcomas. Although senescence plays an important role in the progression of various tumors, its molecular profile remains unclear in STS. Methods: We identified the senescence-related genes (SRGs) in database and depicted characteristics of genomic and transcriptomic profiling using cohort within TCGA and GEO database. In order to investigate the expression of SRGs in different cellular subtypes, single-cell RNA sequencing data was applied. The qPCR and our own sequencing data were utilized for further validation. We used unsupervised consensus clustering analysis to establish senescence-related clusters and subtypes. A senescence scoring system was established by using principal component analysis (PCA). The evaluation of clinical and molecular characteristics was conducted among distinct groups. Results: These SRGs showed differences in SCNV, mutation and mRNA expression in STS tissues compared to normal tissues. Across several cancer types, certain shared features of SRGs were identified. Several SRGs closely correlated with immune cell infiltration. Four clusters related to senescence and three subtypes related to senescence, each with unique clinical and biological traits, were established. The senescence scoring system exhibited effectiveness in predicting outcomes, clinical traits, infiltrations of immune cells and immunotherapy responses. Conclusion: Overall, the current study provided a comprehensive review of molecular profiling for SRGs in STS. The SRGs based clustering and scoring model could help guiding the clinical management of STS.

Deciphering the role of NETosis-related signatures in the prognosis and immunotherapy of soft-tissue sarcoma using machine learning

Background: Soft-tissue sarcomas (STSs) are a rare type of cancer, accounting for about 1% of all adult cancers. Treatments for STSs can be difficult to implement because of their diverse histological and molecular features, which lead to variations in tumor behavior and response to therapy. Despite the growing importance of NETosis in cancer diagnosis and treatment, researches on its role in STSs remain limited compared to other cancer types. Methods: The study thoroughly investigated NETosis-related genes (NRGs) in STSs using large cohorts from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis and Support Vector Machine Recursive Feature Elimination (SVM-RFE) were employed for screening NRGs. Utilizing single-cell RNA-seq (scRNA-seq) dataset, we elucidated the expression profiles of NRGs within distinct cellular subpopulations. Several NRGs were validated by quantitative PCR (qPCR) and our proprietary sequencing data. To ascertain the impact of NRGs on the sarcoma phenotype, we conducted a series of in vitro experimental investigations. Employing unsupervised consensus clustering analysis, we established the NETosis clusters and respective NETosis subtypes. By analyzing DEGs between NETosis clusters, an NETosis scoring system was developed. Results: By comparing the outcomes obtained from LASSO regression analysis and SVM-RFE, 17 common NRGs were identified. The expression levels of the majority of NRGs exhibited notable dissimilarities between STS and normal tissues. The correlation with immune cell infiltration were demonstrated by the network comprising 17 NRGs. Patients within various NETosis clusters and subtypes exhibited different clinical and biological features. The prognostic and immune cell infiltration predictive capabilities of the scoring system were deemed efficient. Furthermore, the scoring system demonstrated potential for predicting immunotherapy response. Conclusion: The current study presents a systematic analysis of NETosis-related gene patterns in STS. The results of our study highlight the critical role NRGs play in tumor biology and the potential for personalized therapeutic approaches through the application of the NETosis score model in STS patients.

Targeted in silico characterization of fusion transcripts in tumor and normal tissues via FusionInspector

Here, we present FusionInspector for in silico characterization and interpretation of candidate fusion transcripts from RNA sequencing (RNA-seq) and exploration of their sequence and expression characteristics. We applied FusionInspector to thousands of tumor and normal transcriptomes and identified statistical and experimental features enriched among biologically impactful fusions. Through clustering and machine learning, we identified large collections of fusions potentially relevant to tumor and normal biological processes. We show that biologically relevant fusions are enriched for relatively high expression of the fusion transcript, imbalanced fusion allelic ratios, and canonical splicing patterns, and are deficient in sequence microhomologies between partner genes. We demonstrate that FusionInspector accurately validates fusion transcripts in silico and helps characterize numerous understudied fusions in tumor and normal tissue samples. FusionInspector is freely available as open source for screening, characterization, and visualization of candidate fusions via RNA-seq, and facilitates transparent explanation and interpretation of machine-learning predictions and their experimental sources.

Immunotherapy resistance driven by loss of NY-ESO-1 expression in response to transgenic adoptive cellular therapy with PD-1 blockade

BACKGROUND

The tumor antigen NY-ESO-1 has been shown to be an effective target for transgenic adoptive cell therapy (ACT) for the treatment of sarcoma and melanoma. However, despite frequent early clinical responses, many patients ultimately develop progressive disease. Understanding the mechanisms underlying treatment resistance is crucial to improve future ACT protocols. Here, we describe a novel mechanism of treatment resistance in sarcoma involving loss of expression of NY-ESO-1 in response to transgenic ACT with dendritic cell (DC) vaccination and programmed cell death protein-1 (PD-1) blockade.

METHODS

A HLA-A*02:01-positive patient with an NY-ESO-1-positive undifferentiated pleomorphic sarcoma was treated with autologous NY-ESO-1-specific T-cell receptor (TCR) transgenic lymphocytes, NY-ESO-1 peptide-pulsed DC vaccination, and nivolumab-mediated PD-1 blockade.

RESULTS

Peripheral blood reconstitution with NY-ESO-1-specific T cells peaked within 2 weeks of ACT, indicating rapid in vivo expansion. There was initial tumor regression, and immunophenotyping of the peripheral transgenic T cells showed a predominantly effector memory phenotype over time. Tracking of transgenic T cells to the tumor sites was demonstrated in on-treatment biopsy via both TCR sequencing-based and RNA sequencing-based immune reconstitution, and nivolumab binding to PD-1 on transgenic T cells was confirmed at the tumor site. At the time of disease progression, the promoter region of NY-ESO-1 was found to be extensively methylated, and tumor NY-ESO-1 expression was completely lost as measured by RNA sequencing and immunohistochemistry.

CONCLUSIONS

ACT of NY-ESO-1 transgenic T cells given with DC vaccination and anti-PD-1 therapy resulted in transient antitumor activity. NY-ESO-1 expression was lost in the post-treatment sample in the setting of extensive methylation of the NY-ESO-1 promoter region.

BIOLOGICAL/CLINICAL INSIGHT

Antigen loss represents a novel mechanism of immune escape in sarcoma and a new point of improvement in cellular therapy approaches.

TRIAL REGISTRATION NUMBER

NCT02775292.

Synovial Sarcoma Preclinical Modeling: Integrating Transgenic Mouse Models and Patient-Derived Models for Translational Research

Synovial sarcomas (SyS) are rare malignant tumors predominantly affecting children, adolescents, and young adults. The genetic hallmark of SyS is the t(X;18) translocation encoding the SS18-SSX fusion gene. The fusion protein interacts with both the BAF enhancer and polycomb repressor complexes, and either activates or represses target gene transcription, resulting in genome-wide epigenetic perturbations and altered gene expression. Several experimental in in vivo models, including conditional transgenic mouse models expressing the SS18-SSX fusion protein and spontaneously developing SyS, are available. In addition, patient-derived xenografts have been estab-lished in immunodeficient mice, faithfully reproducing the complex clinical heterogeneity. This review focuses on the main molecular features of SyS and the related preclinical in vivo and in vitro models. We will analyze the different conditional SyS mouse models that, after combination with some of the few other recurrent alterations, such as gains in BCL2, Wnt-β-catenin signaling, FGFR family, or loss of PTEN and SMARCB1, have provided additional insight into the mechanisms of synovial sarcomagenesis. The recent advancements in the understanding of SyS biology and improvements in preclinical modeling pave the way to the development of new epigenetic drugs and immunotherapeutic approaches conducive to new treatment options.

An inflammatory state remodels the immune microenvironment and improves risk stratification in acute myeloid leukemia

Acute myeloid leukemia (AML) is a hematopoietic malignancy with poor prognosis and limited treatment options. Here we provide a comprehensive census of the bone marrow immune microenvironment in adult and pediatric patients with AML. We characterize unique inflammation signatures in a subset of AML patients, associated with inferior outcomes. We identify atypical B cells, a dysfunctional B-cell subtype enriched in patients with high-inflammation AML, as well as an increase in CD8+GZMK+ and regulatory T cells, accompanied by a reduction in T-cell clonal expansion. We derive an inflammation-associated gene score (iScore) that associates with poor survival outcomes in patients with AML. Addition of the iScore refines current risk stratifications for patients with AML and may enable identification of patients in need of more aggressive treatment. This work provides a framework for classifying patients with AML based on their immune microenvironment and a rationale for consideration of the inflammatory state in clinical settings.

Identification of anoikis-related molecular patterns to define tumor microenvironment and predict immunotherapy response and prognosis in soft-tissue sarcoma

Background: Soft-tissue sarcoma (STS) is a massive threat to human health due to its high morbidity and malignancy. STS also represents more than 100 histologic and molecular subtypes, with different prognosis. There is growing evidence that anoikis play a key role in the proliferation and invasion of tumors. However, the effects of anoikis in the immune landscape and the prognosis of STS remain unclear. Methods: We analyzed the genomic and transcriptomic profiling of 34 anoikis-related genes (ARGs) in patient cohort of pan-cancer and STS from The Cancer Genome Atlas (TCGA) database. Single-cell transcriptome was used to disclose the expression patterns of ARGs in specific cell types. Gene expression was further validated by real-time PCR and our own sequencing data. We established the Anoikis cluster and Anoikis subtypes by using unsupervised consensus clustering analysis. An anoikis scoring system was further built based on the differentially expressed genes (DEGs) between Anoikis clusters. The clinical and biological characteristics of different groups were evaluated. Results: The expressions of most ARGs were significantly different between STS and normal tissues. We found some common ARGs profiles across the pan-cancers. Network of 34 ARGs demonstrated the regulatory pattern and the association with immune cell infiltration. Patients from different Anoikis clusters or Anoikis subtypes displayed distinct clinical and biological characteristics. The scoring system was efficient in prediction of prognosis and immune cell infiltration. In addition, the scoring system could be used to predict immunotherapy response. Conclusion: Overall, our study thoroughly depicted the anoikis-related molecular and biological profiling and interactions of ARGs in STS. The Anoikis score model could guide the individualized management.

Distinct gene mutation profiles among multiple and single primary lung adenocarcinoma

With the development of technologies, multiple primary lung cancer (MPLC) has been detected more frequently. Although large-scale genomics studies have made significant progress, the aberrant gene mutation in MPLC is largely unclear. In this study, 141 and 44 lesions from single and multiple primary lung adenocarcinoma (SP- and MP-LUAD) were analyzed. DNA and RNA were extracted from formalin-fixed, paraffin-embedded tumor tissue and sequenced by using the next-generation sequencing-based YuanSu450TM gene panel. We systematically analyzed the clinical features and gene mutations of these lesions, and found that there were six genes differently mutated in MP-LUAD and SP-LUAD lesions, including RBM10, CDK4, ATRX, NTRK1, PREX2, SS18. Data from the cBioPortal database indicated that mutation of these genes was related to some clinical characteristics, such as TMB, tumor type, et al. Besides, heterogeneity analysis suggested that different lesions could be tracked back to monophyletic relationships. We compared the mutation landscape of MP-LUAD and SP-LUAD and identified six differentially mutated genes (RBM10, CDK4, ATRX, NTRK1, PREX2, SS18), and certain SNV loci in TP53 and EGFR which might play key roles in lineage decomposition in multifocal samples. These findings may provide insight into personalized prognosis prediction and new therapies for MP-LUAD patients.

Impact of the Human Cell Atlas on medicine

Single-cell atlases promise to provide a 'missing link' between genes, diseases and therapies. By identifying the specific cell types, states, programs and contexts where disease-implicated genes act, we will understand the mechanisms of disease at the cellular and tissue levels and can use this understanding to develop powerful disease diagnostics; identify promising new drug targets; predict their efficacy, toxicity and resistance mechanisms; and empower new kinds of therapies, from cancer therapies to regenerative medicine. Here, we lay out a vision for the potential of cell atlases to impact the future of medicine, and describe how advances over the past decade have begun to realize this potential in common complex diseases, infectious diseases (including COVID-19), rare diseases and cancer.

Developmental Deconvolution for Classification of Cancer Origin

Cancer is partly a developmental disease, with malignancies named based on cell or tissue of origin. However, a systematic atlas of tumor origins is lacking. Here we map the single-cell organogenesis of 56 developmental trajectories to the transcriptomes of over 10,000 tumors across 33 cancer types. We deconvolute tumor transcriptomes into signals for individual developmental trajectories. Using these signals as inputs, we construct a developmental multilayer perceptron (D-MLP) classifier that outputs cancer origin. D-MLP (ROC-AUC: 0.974 for top prediction) outperforms benchmark classifiers. We analyze tumors from patients with cancer of unknown primary (CUP), selecting the most difficult cases in which extensive multimodal workup yielded no definitive tumor type. Interestingly, CUPs form groups distinguished by developmental trajectories, and classification reveals diagnosis for patient tumors. Our results provide an atlas of tumor developmental origins, provide a tool for diagnostic pathology, and suggest developmental classification may be a useful approach for patient tumors.

SIGNIFICANCE

Here we map the developmental trajectories of tumors. We deconvolute tumor transcriptomes into signals for mammalian developmental programs and use this information to construct a deep learning classifier that outputs tumor type. We apply the classifier to CUP and reveal the developmental origins of patient tumors. See related commentary by Wang, p. 2498. This article is highlighted in the In This Issue feature, p. 2483.

Clinical application of advanced multi-omics tumor profiling: Shaping precision oncology of the future

Next-generation DNA sequencing technology has dramatically advanced clinical oncology through the identification of therapeutic targets and molecular biomarkers, leading to the personalization of cancer treatment with significantly improved outcomes for many common and rare tumor entities. More recent developments in advanced tumor profiling now enable dissection of tumor molecular architecture and the functional phenotype at cellular and subcellular resolution. Clinical translation of high-resolution tumor profiling and integration of multi-omics data into precision treatment, however, pose significant challenges at the level of prospective validation and clinical implementation. In this review, we summarize the latest advances in multi-omics tumor profiling, focusing on spatial genomics and chromatin organization, spatial transcriptomics and proteomics, liquid biopsy, and ex vivo modeling of drug response. We analyze the current stages of translational validation of these technologies and discuss future perspectives for their integration into precision treatment.

Biomarker correlates with response to NY-ESO-1 TCR T cells in patients with synovial sarcoma

Autologous T cells transduced to express a high affinity T-cell receptor specific to NY-ESO-1 (letetresgene autoleucel, lete-cel) show promise in the treatment of metastatic synovial sarcoma, with 50% overall response rate. The efficacy of lete-cel treatment in 45 synovial sarcoma patients (NCT01343043) has been previously reported, however, biomarkers predictive of response and resistance remain to be better defined. This post-hoc analysis identifies associations of response to lete-cel with lymphodepleting chemotherapy regimen (LDR), product attributes, cell expansion, cytokines, and tumor gene expression. Responders have higher IL-15 levels pre-infusion (p = 0.011) and receive a higher number of transduced effector memory (CD45RA- CCR7-) CD8 + cells per kg (p = 0.039). Post-infusion, responders have increased IFNγ, IL-6, and peak cell expansion (p < 0.01, p < 0.01, and p = 0.016, respectively). Analysis of tumor samples post-treatment illustrates lete-cel infiltration and a decrease in expression of macrophage genes, suggesting remodeling of the tumor microenvironment. Here we report potential predictive and pharmacodynamic markers of lete-cel response that may inform LDR, cell dose, and strategies to enhance anticancer efficacy.

Biomarkers predictive of response to T cell therapy remain to be better defined. This study identifies potential predictive and pharmacodynamic markers of response to NY-ESO-1 T-cell therapy in a solid tumor that may inform lymphodepletion, cell dose, and strategies to enhance anticancer efficacy.

Pathogenic Roles of RNA-Binding Proteins in Sarcomas

RNA-binding proteins (RBPs) are proteins that physically and functionally bind to RNA to regulate the RNA metabolism such as alternative splicing, polyadenylation, transport, maintenance of stability, localization, and translation. There is accumulating evidence that dysregulated RBPs play an essential role in the pathogenesis of malignant tumors including a variety of types of sarcomas. On the other hand, prognosis of patients with sarcoma, especially with sarcoma in advanced stages, is very poor, and almost no effective standard treatment has been established for most of types of sarcomas so far, highlighting the urgent need for identifying novel therapeutic targets based on the deep understanding of pathogenesis. Therefore, defining the network of interactions between RBPs and disease-related RNA targets will contribute to a better understanding of sarcomagenesis and identification of a novel therapeutic target for sarcomas.

Recombinant DTβ4-inspired porous 3D vascular graft enhanced antithrombogenicity and recruited circulating CD93+/CD34+ cells for endothelialization

Matching material degradation with host remodeling, including endothelialization and muscular remodeling, is important to vascular regeneration. We fabricated 3D PGS-PCL vascular grafts, which presented tunable polymer components, porosity, mechanical strength, and degrading rate. Furthermore, highly porous structures enabled 3D patterning of conjugated heparin-binding peptide, dimeric thymosin β4 (DTβ4), which played key roles in antiplatelets, fibrinogenesis inhibition, and recruiting circulating progenitor cells, thereafter contributed to high patency rate, and unprecedentedly acquired carotid arterial regeneration in rabbit model. Through single-cell RNA sequencing analysis and cell tracing studies, a subset of endothelial progenitor cells, myeloid-derived CD93⁺/CD34⁺ cells, was identified as the main contributor to final endothelium regeneration. To conclude, DTβ4-inspired porous 3DVGs present adjustable physical properties, superior anticoagulating, and re-endothelializing potentials, which leads to the regeneration of small-caliber artery, thus offering a promising tool for vessel replacement in clinical applications.

Cross-Talk of Multiple Types of RNA Modification Regulators Uncovers the Tumor Microenvironment and Immune Infiltrates in Soft Tissue Sarcoma

Background

Soft-tissue sarcoma (STS) represents a rare and diverse cohort of solid tumors, and encompasses over 100 various histologic and molecular subtypes. In recent years, RNA modifications including m6A, m5C, m1A, and m7G have been demonstrated to regulate immune response and tumorigenesis. Nevertheless, the cross-talk among these RNA modification regulators and related effects upon the tumor microenvironment (TME), immune infiltrates, and immunotherapy in STS remain poorly understood.

Methods

In this study, we comprehensively investigated transcriptional and genetic alterations of 32 RNA modification regulators in STS patients from The Cancer Genome Atlas (TCGA) cohort and validated them in the Gene Expression Omnibus (GEO) cohort. Single-cell transcriptomes were introduced to identify regulators within specific cell types, with own sequencing data and RT-qPCR conducted for biological validation. Distinct regulator clusters and regulator gene subtypes were identified by using unsupervised consensus clustering analysis. We further built the regulator score model based on the prognostic regulator-related differentially expressed genes (DEGs), which could be used to quantitatively assess the risk for individual STS patients. The clinical and biological characteristics of different regulator score groups were further examined.

Results

A total of 455 patients with STS were included in this analysis. The network of 32 RNA modification regulators demonstrated significant correlations within multiple different RNA modification types. Distinct regulator clusters and regulator gene subtypes were characterized by markedly different prognoses and TME landscapes. The low regulator score group in the TCGA-SARC cohort was characterized by poor prognosis. The robustness of the scoring model was further confirmed by the external validation in GSE30929 and GSE17674. The regulator score was negatively correlated with CD4+ T cell, Th2 cell, and Treg cell recruitment and most immunotherapy-predicted pathways, and was also associated with immunotherapy efficacy.

Conclusions

Overall, our study is the first to demonstrate the cross-talk of RNA modification regulators and the potential roles in TME and immune infiltrates in STS. The individualized assessment based on the regulator score model could facilitate and optimize personalized treatment.

Single cell- and spatial 'Omics revolutionize physiology

Single cell multi- 'Omics and Spatial Transcriptomics are prominent technological highlights of recent years, and both fields still witness a ceaseless firework of novel approaches for high resolution profiling of additional omics layers. As all life processes in organs and organisms are based on the functions of their fundamental building blocks, the individual cells and their interactions, these methods are of utmost worth for the study of physiology in health and disease. Recent discoveries on embryonic development, tumor immunology, the detailed cellular composition and function of complex tissues like for example the kidney or the brain, different roles of the same cell type in different organs, the oncogenic program of individual tumor entities, or the architecture of immunopathology in infected tissue are based on single cell and spatial transcriptomics experiments. In this review, we will give a broad overview of technological concepts for single cell and spatial analysis, showing both advantages and limitations, and illustrate their impact with some particularly impressive case studies.

Identifying tumor cells at the single-cell level using machine learning

Tumors are complex tissues of cancerous cells surrounded by a heterogeneous cellular microenvironment with which they interact. Single-cell sequencing enables molecular characterization of single cells within the tumor. However, cell annotation—the assignment of cell type or cell state to each sequenced cell—is a challenge, especially identifying tumor cells within single-cell or spatial sequencing experiments. Here, we propose ikarus, a machine learning pipeline aimed at distinguishing tumor cells from normal cells at the single-cell level. We test ikarus on multiple single-cell datasets, showing that it achieves high sensitivity and specificity in multiple experimental contexts.

The Molecular Biology of Soft Tissue Sarcomas: Current Knowledge and Future Perspectives

Simple Summary

Over the past 20 years, significant advances in the field of genetics and molecular biology have led to the dismantlement of multiple subtypes of sarcomas. As a result, molecular approaches nowadays play a critical role in the diagnosis, prognostic classification, and therapeutic management of numerous mesenchymal tumor subtypes. This review of the current literature illustrates the main uses of molecular biology in the field of soft tissue sarcomas and the future challenges that remain to be addressed.

Abstract

Soft tissue sarcomas are malignant tumors of mesenchymal origin, encompassing a large spectrum of entities that were historically classified according to their histological characteristics. Over the last decades, molecular biology has allowed a better characterization of these tumors, leading to the incorporation of multiple molecular features in the latest classification of sarcomas as well as to molecularly-guided therapeutic strategies. This review discusses the main uses of molecular biology in current practice for the diagnosis and treatment of soft tissue sarcomas, in addition to perspectives for this rapidly evolving field of research.

Pediatric Sarcomas: The Next Generation of Molecular Studies

Simple Summary

There has been an incredible amount of discovery in pediatric sarcomas, but much remains to be accomplished. Clinical challenges include diagnostic heterogeneity and the poor outcome of patients with high risk, metastatic, and relapsed disease. The emergence of single cell sequencing has allowed the ability to document tumor cell heterogeneity in amazing detail, but it does not allow the ability to visualize spatial orientation. This problem has been solved by spatial multi-omics, which can be used to map tumors and visualize the distribution of critical transcripts, mutations, and proteins. However, these tools only offer observational data. High-throughput functional genomics provides a powerful way to highlight oncogenic drivers and potential therapy opportunities. Research has been hamstrung by a need for annotated specimens, particularly in post-therapy, relapsed, and metastatic disease, and initial biopsies offer only limited data opportunities. Data complexity, variability, and inconsistency present problems best approached with AI/machine learning. We stand on the threshold of a revolution in cancer cell biology that has the potential for translation into more effective and more directed therapies, particularly for previously recalcitrant diseases.

Abstract

Pediatric sarcomas constitute one of the largest groups of childhood cancers, following hematopoietic, neural, and renal lesions. Partly because of their diversity, they continue to offer challenges in diagnosis and treatment. In spite of the diagnostic, nosologic, and therapeutic gains made with genetic technology, newer means for investigation are needed. This article reviews emerging technology being used to study human neoplasia and how these methods might be applicable to pediatric sarcomas. Methods reviewed include single cell RNA sequencing (scRNAseq), spatial multi-omics, high-throughput functional genomics, and clustered regularly interspersed short palindromic sequence-Cas9 (CRISPR-Cas9) technology. In spite of these advances, the field continues to be challenged by a dearth of properly annotated materials, particularly from recurrences and metastases and pre- and post-treatment samples.

DIALOGUE maps multicellular programs in tissue from single-cell or spatial transcriptomics data

Deciphering the functional interactions of cells in tissues remains a major challenge. We describe DIALOGUE, a method to systematically uncover multicellular programs (MCPs) — combinations of coordinated cellular programs in different cell types that form higher-order functional units at the tissue level — from either spatial data or single-cell data obtained without spatial information. Tested on spatial datasets from the mouse hypothalamus, cerebellum, visual cortex, and neocortex, DIALOGUE identified MCPs associated with animal behavior and recovered spatial properties when tested on unseen data, while outperforming other methods and metrics. In spatial data from human lung cancer, DIALOGUE identified MCPs marking immune activation and tissue remodeling. Applied to scRNA-seq data across individuals or regions, DIALOGUE uncovered MCPs in Alzheimer’s disease, ulcerative colitis, and treatment with cancer immunotherapy. These programs were predictive of disease outcome and predisposition in independent cohorts and included risk genes from genome-wide association studies (GWAS). DIALOGUE enables the analysis of multicellular regulation in health and disease.

Coordinated gene programs spanning multiple different cell types are identified in healthy and diseased tissues.

Oncogenic chimeric transcription factors drive tumor-specific transcription, processing, and translation of silent genomic regions

Many cancers are characterized by gene fusions encoding oncogenic chimeric transcription factors (TFs) such as EWS::FLI1 in Ewing sarcoma (EwS). Here, we find that EWS::FLI1 induces the robust expression of a specific set of novel spliced and polyadenylated transcripts within otherwise transcriptionally silent regions of the genome. These neogenes (NGs) are virtually undetectable in large collections of normal tissues or non-EwS tumors and can be silenced by CRISPR interference at regulatory EWS::FLI1-bound microsatellites. Ribosome profiling and proteomics further show that some NGs are translated into highly EwS-specific peptides. More generally, we show that hundreds of NGs can be detected in diverse cancers characterized by chimeric TFs. Altogether, this study identifies the transcription, processing, and translation of novel, specific, highly expressed multi-exonic transcripts from otherwise silent regions of the genome as a new activity of aberrant TFs in cancer.

HLA Class I Analysis Provides Insight Into the Genetic and Epigenetic Background of Immune Evasion in Colorectal Cancer With High Microsatellite Instability

BACKGROUND & AIMS

A detailed understanding of antitumor immunity is essential for optimal cancer immune therapy. Although defective mutations in the B2M and HLA-ABC genes, which encode molecules essential for antigen presentation, have been reported in several studies, the effects of these defects on tumor immunity have not been quantitatively evaluated.

METHODS

Mutations in HLA-ABC genes were analyzed in 114 microsatellite instability-high colorectal cancers using a long-read sequencer. The data were further analyzed in combination with whole-exome sequencing, transcriptome sequencing, DNA methylation array, and immunohistochemistry data.

RESULTS

We detected 101 truncating mutations in 57 tumors (50%) and loss of 61 alleles in 21 tumors (18%). Based on the integrated analysis that enabled the immunologic subclassification of microsatellite instability-high colorectal cancers, we identified a subtype of tumors in which lymphocyte infiltration was reduced, partly due to reduced expression of HLA-ABC genes in the absence of apparent genetic alterations. Survival time of patients with such tumors was shorter than in patients with other tumor types. Paradoxically, tumor mutation burden was highest in the subtype, suggesting that the immunogenic effect of accumulating mutations was counterbalanced by mutations that weakened immunoreactivity. Various genetic and epigenetic alterations, including frameshift mutations in RFX5 and promoter methylation of PSMB8 and HLA-A, converged on reduced expression of HLA-ABC genes.

CONCLUSIONS

Our detailed immunogenomic analysis provides information that will facilitate the improvement and development of cancer immunotherapy.

Current Status and Future Directions of Immunotherapies in Soft Tissue Sarcomas

Immunotherapy in soft tissue sarcoma (STS) has experienced a surge of interest in the past decade, contributing to an expanding number of therapeutic options for this extremely heterogenous group of rare malignancies. Immune checkpoint inhibitors (CPIs) targeting the PD-1 and CTLA-4 axes have demonstrated promising responses in a select number of STS subtypes, including rarer subtypes, such as alveolar soft part sarcoma, SWI/SNF-deficient sarcomas, clear cell sarcoma, and angiosarcoma. Multiple pan-subtype sarcoma trials have facilitated the study of possible predictive biomarkers of the CPI response. It has also become apparent that certain therapies, when combined with CPIs, can enhance response rates, although the specific mechanisms of this possible synergy remain unconfirmed in STS. In addition to CPIs, several other immune targeting agents, including anti-tumour-associated macrophage and antigen-directed therapies, are now under assessment in STS with promising efficacy in some subtypes. In this article, we review the state of the art in immunotherapy in STS, highlighting the pre-clinical and clinical data available for this promising therapeutic strategy.

Upregulation of ERK-EGR1-heparanase axis by HDAC inhibitors provides targets for rational therapeutic intervention in synovial sarcoma

BACKGROUND

Synovial sarcoma (SS) is an aggressive soft tissue tumor with limited therapeutic options in advanced stage. SS18-SSX fusion oncogenes, which are the hallmarks of SS, cause epigenetic rewiring involving histone deacetylases (HDACs). Promising preclinical studies supporting HDAC targeting for SS treatment were not reflected in clinical trials with HDAC inhibitor (HDACi) monotherapies. We investigated pathways implicated in SS cell response to HDACi to identify vulnerabilities exploitable in combination treatments and improve the therapeutic efficacy of HDACi-based regimens.

METHODS

Antiproliferative and proapoptotic effects of the HDACi SAHA and FK228 were examined in SS cell lines in parallel with biochemical and molecular analyses to bring out cytoprotective pathways. Treatments combining HDACi with drugs targeting HDACi-activated prosurvival pathways were tested in functional assays in vitro and in a SS orthotopic xenograft model. Molecular mechanisms underlying synergisms were investigated in SS cells through pharmacological and gene silencing approaches and validated by qRT-PCR and Western blotting.

RESULTS

SS cell response to HDACi was consistently characterized by activation of a cytoprotective and auto-sustaining axis involving ERKs, EGR1, and the β-endoglycosidase heparanase, a well recognized pleiotropic player in tumorigenesis and disease progression. HDAC inhibition was shown to upregulate heparanase by inducing expression of the positive regulator EGR1 and by hampering negative regulation by p53 through its acetylation. Interception of HDACi-induced ERK-EGR1-heparanase pathway by cell co-treatment with a MEK inhibitor (trametinib) or a heparanase inhibitor (SST0001/roneparstat) enhanced antiproliferative and pro-apoptotic effects. HDAC and heparanase inhibitors had opposite effects on histone acetylation and nuclear heparanase levels. The combination of SAHA with SST0001 prevented the upregulation of ERK-EGR1-heparanase induced by the HDACi and promoted caspase-dependent cell death. In vivo, the combined treatment with SAHA and SST0001 potentiated the antitumor efficacy against the CME-1 orthotopic SS model as compared to single agent administration.

CONCLUSIONS

The present study provides preclinical rationale and mechanistic insights into drug combinatory strategies based on the use of ERK pathway and heparanase inhibitors to improve the efficacy of HDACi-based antitumor therapies in SS. The involvement of classes of agents already clinically available, or under clinical evaluation, indicates the transferability potential of the proposed approaches.

Visualizing in deceased COVID-19 patients how SARS-CoV-2 attacks the respiratory and olfactory mucosae but spares the olfactory bulb

Anosmia, the loss of smell, is a common and often the sole symptom of COVID-19. The onset of the sequence of pathobiological events leading to olfactory dysfunction remains obscure. Here, we have developed a postmortem bedside surgical procedure to harvest endoscopically samples of respiratory and olfactory mucosae and whole olfactory bulbs. Our cohort of 85 cases included COVID-19 patients who died a few days after infection with SARS-CoV-2, enabling us to catch the virus while it was still replicating. We found that sustentacular cells are the major target cell type in the olfactory mucosa. We failed to find evidence for infection of olfactory sensory neurons, and the parenchyma of the olfactory bulb is spared as well. Thus, SARS-CoV-2 does not appear to be a neurotropic virus. We postulate that transient insufficient support from sustentacular cells triggers transient olfactory dysfunction in COVID-19. Olfactory sensory neurons would become affected without getting infected.

Application of Single-Cell Multi-Omics in Dissecting Cancer Cell Plasticity and Tumor Heterogeneity

Tumor heterogeneity, a hallmark of cancer, impairs the efficacy of cancer therapy and drives tumor progression. Exploring inter- and intra-tumoral heterogeneity not only provides insights into tumor development and progression, but also guides the design of personalized therapies. Previously, high-throughput sequencing techniques have been used to investigate the heterogeneity of tumor ecosystems. However, they could not provide a high-resolution landscape of cellular components in tumor ecosystem. Recently, advance in single-cell technologies has provided an unprecedented resolution to uncover the intra-tumoral heterogeneity by profiling the transcriptomes, genomes, proteomes and epigenomes of the cellular components and also their spatial distribution, which greatly accelerated the process of basic and translational cancer research. Importantly, it has been demonstrated that some cancer cells are able to transit between different states in order to adapt to the changing tumor microenvironment, which led to increased cellular plasticity and tumor heterogeneity. Understanding the molecular mechanisms driving cancer cell plasticity is critical for developing precision therapies. In this review, we summarize the recent progress in dissecting the cancer cell plasticity and tumor heterogeneity by use of single-cell multi-omics techniques.