Modularized supramolecular assemblies for hypoxia-activatable fluorescent visualization and image-guided theranostics.

Rationale: Molecular imaging of microenvironment by hypoxia-activatable fluorescence probes has emerged as an attractive approach to tumor diagnosis and image-guided treatment. Difficulties remain in its translational applications due to hypoxia heterogeneity in tumor microenvironments, making it challenging to image hypoxia as a reliable proxy of tumor distribution. Methods: We report a modularized theranostics platform to fluorescently visualize hypoxia via light-modulated signal compensation to overcome tumor heterogeneity, thereby serving as a diagnostic tool for image-guided surgical resection and photodynamic therapy. Specifically, the platform integrating dual modules of fluorescence indicator and photodynamic moderator using supramolecular host-guest self-assembly, which operates cooperatively as a cascaded "AND" logic gate. First, tumor enrichment and specific fluorescence turn-on in hypoxic regions were accessible via tumor receptors and cascaded microenvironment signals as simultaneous inputs of the "AND" gate. Second, image guidance by a lighted fluorescence module and light-mediated endogenous oxygen consumption of a photodynamic module as dual inputs of "AND" gate collaboratively enabled light-modulated signal compensation in situ, indicating homogeneity of enhanced hypoxia-related fluorescence signals throughout a tumor. Results: In in vitro and in vivo analyses, the biocompatible platform demonstrated several strengths including a capacity for dual tumor targeting to progressively facilitate specific fluorescence turn-on, selective signal compensation, imaging-time window extension conducive to precise normalized image-guided treatment, and the functionality of tumor glutathione depletion to improve photodynamic efficacy. Conclusion: The hypoxia-activatable, image-guided theranostic platform demonstrated excellent potential for overcoming hypoxia heterogeneity in tumors.

A Probabilistic Approach to Estimate the Temporal Order of Pathway Mutations Accounting for Intra-Tumor Heterogeneity.

The development of cancer involves the accumulation of somatic mutations in several essential biological pathways. Delineating the temporal order of pathway mutations during tumorigenesis is crucial for comprehending the biological mechanisms underlying cancer development and identifying potential targets for therapeutic intervention. Several computational and statistical methods have been introduced for estimating the order of somatic mutations based on mutation profile data from a cohort of patients. However, one major issue of current methods is that they do not take into account intra-tumor heterogeneity (ITH), which limits their ability to accurately discern the order of pathway mutations. To address this problem, we propose PATOPAI, a probabilistic approach to estimate the temporal order of mutations at the pathway level by incorporating ITH information as well as pathway and functional annotation information of mutations. PATOPAI uses a maximum likelihood approach to estimate the probability of pathway mutational events occurring in a specific sequence, wherein it focuses on the orders that are consistent with the phylogenetic structure of the tumors. Applications to whole exome sequencing data from The Cancer Genome Atlas (TCGA) illustrate our method's ability to recover the temporal order of pathway mutations in several cancer types.

Metabolic Vulnerabilities in Cancer: A New Therapeutic Strategy.

Cancer metabolism is now a key area for therapeutic intervention, targeting unique metabolic reprogramming crucial for tumor growth and survival. This article reviews the therapeutic potential of addressing metabolic vulnerabilities through glycolysis and glutaminase inhibitors, which disrupt cancer cell metabolism. Challenges such as tumor heterogeneity and adaptive resistance are discussed, with strategies including personalized medicine and predictive biomarkers to enhance treatment efficacy. Additionally, integrating diet and lifestyle changes with metabolic targeting underscores a holistic approach to improving therapy outcomes. The article also examines the benefits of incorporating these strategies into standard care, highlighting the potential for more tailored, safer treatments. In conclusion, exploiting metabolic vulnerabilities promises a new era in oncology, positioning metabolic targeting at the forefront of personalized cancer therapy and transforming patient care.

Effect of Bioactive Black Phosphorus Nanomaterials on Cancer-Associated Fibroblast Heterogeneity in Pancreatic Cancer.

Tumor-stromal interactions and stromal heterogeneity in the tumor microenvironment are critical factors that influence the progression, metastasis, and chemoresistance of pancreatic ductal adenocarcinoma (PDAC). Here, we used spatial transcriptome technology to profile the gene expression landscape of primary PDAC and liver metastatic PDAC after bioactive black phosphorus nanomaterial (bioactive BP) treatment using a murine model of PDAC (LSL-KrasG12D/+; LSL-Trp53R172H/+; and Pdx-1-Cre mice). Bioinformatic and biochemical analyses showed that bioactive BP contributes to the tumor-stromal interplay by suppressing cancer-associated fibroblast (CAF) activation. Our results showed that bioactive BP contributes to CAF heterogeneity by decreasing the amount of inflammatory CAFs and myofibroblastic CAFs, two CAF subpopulations. Our study demonstrates the influence of bioactive BP on tumor-stromal interactions and CAF heterogeneity and suggests bioactive BP as a potential PDAC treatment.

Accumulation of liposomes in metastatic tumor sites is not necessary for anti-cancer drug efficacy.

BACKGROUND: The tumor microenvironment is profoundly heterogeneous particularly when comparing sites of metastases. Establishing the extent of this heterogeneity may provide guidance on how best to design lipid-based drug delivery systems to treat metastatic disease. Building on our previous research, the current study employs a murine model of metastatic cancer to explore the distribution of ~ 100 nm liposomes. METHODS: Female NCr nude mice were inoculated with a fluorescently labeled, Her2/neu-positive, trastuzumab-resistant breast cancer cell line, JIMT-1mkate, either in the mammary fat pad to create an orthotopic tumor (OT), or via intracardiac injection (IC) to establish tumors throughout the body. Animals were dosed with fluorescent and radio-labeled liposomes. In vivo and ex vivo fluorescent imaging was used to track liposome distribution over a period of 48 h. Liposome distribution in orthotopic tumors was compared to sites of tumor growth that arose following IC injection. RESULTS: A significant amount of inter-vessel heterogeneity for DiR distribution was observed, with most tumor blood vessels showing little to no presence of the DiR-labelled liposomes. Further, there was limited extravascular distribution of DiR liposomes in the perivascular regions around DiR-positive vessels. While all OT tumors contained at least some DiR-positive vessels, many metastases had very little or none. Despite the apparent limited distribution of liposomes within metastases, two liposomal drug formulations, Irinophore C and Doxil, showed similar efficacy for both the OT and IC JIMT-1mkate models. CONCLUSION: These findings suggest that liposomal formulations achieve therapeutic benefits through mechanisms that extend beyond the enhanced permeability and retention effect.

Resistance to immune checkpoint inhibitors in colorectal cancer with deficient mismatch repair/microsatellite instability: misdiagnosis, pseudoprogression and/or tumor heterogeneity?

Colorectal carcinoma (CRC) with deficiency of the deficient mismatch repair (dMMR) pathway/microsatellite instability (MSI) is characterized by a high mutation load and infiltration of immune cells in the tumor microenvironment. In agreement with these findings, clinical trials have demonstrated a significant activity of immune checkpoint inhibitors (ICIs) in dMMR/MSI metastatic CRC (mCRC) patients and, more recently, in CRC patients with early disease undergoing neoadjuvant therapy. However, despite high response rates and durable clinical benefits, a fraction of mCRC patients, up to 30%, showed progressive disease when treated with single agent anti-programmed cell death 1 (PD-1) antibody. This article discusses the three main causes that have been associated with early progression of dMMR/MSI mCRC patients while on treatment with ICIs, i.e., misdiagnosis, pseudoprogression and tumor heterogeneity. While pseudoprogression probably does not play a relevant role, data from clinical studies demonstrate that some dMMR/MSI CRC cases with rapid progression on ICIs may be misdiagnosed, underlining the importance of correct diagnostics. More importantly, evidence suggests that dMMR/MSI mCRC is a heterogeneous group of tumors with different sensitivity to ICIs. Therefore, we propose novel diagnostic and therapeutic strategies to improve the outcome of dMMR/MSI CRC patients.

Genomic profiling of a multi-lineage and multi-passage patient-derived xenograft biobank reflects heterogeneity of ovarian cancer.

Ovarian cancer (OC) manifests as a complex disease characterized by inter- and intra-patient heterogeneity. Despite enhanced biological and genetic insights, OC remains a recalcitrant malignancy with minimal survival improvement. Based on multi-site sampling and a multi-lineage patient-derived xenograft (PDX) establishment strategy, we present herein the establishment of a comprehensive PDX biobank from histologically and molecularly heterogeneous OC patients. Comprehensive profiling of matched PDX and patient samples demonstrates that PDXs closely recapitulate parental tumors. By leveraging multi-lineage models, we reveal that the previously reported genomic disparities of PDX could be mainly attributed to intra-patient spatial heterogeneity instead of substantial model-independent genomic evolution. Moreover, DNA damage response pathway inhibitor (DDRi) screening uncovers heterogeneous responses across models. Prolonged iterative drug exposure recapitulates acquired drug resistance in initially sensitive models. Meanwhile, interrogation of induced drug-resistant (IDR) models reveals that suppressed interferon (IFN) response and activated Wnt/ß-catenin signaling contribute to acquired DDRi drug resistance.

Metabolic Heterogeneity of Tumor Cells and its Impact on Colon Cancer Metastasis: Insights from Single-Cell and Bulk Transcriptome Analyses.

Background: Metabolic reprogramming plays a crucial role in the development of colorectal cancer (CRC), influencing tumor heterogeneity, the tumor microenvironment, and metastasis. While the interaction between metabolism and CRC is critical for developing personalized treatments, gaps remain in understanding how tumor cell metabolism affects prognosis. Our study introduces novel insights by integrating single-cell and bulk transcriptome analyses to explore the metabolic landscape within CRC cells and its mechanisms influencing disease progression. This approach allows us to uncover metabolic heterogeneity and identify specific metabolic genes impacting metastasis, which have not been thoroughly examined in previous studies. Methods: We sourced microarray and single-cell RNA sequencing datasets from the Gene Expression Omnibus (GEO) and bulk sequencing data for CRC from The Cancer Genome Atlas (TCGA). We employed Gene Set Variation Analysis (GSVA) to assess metabolic pathway activity, consensus clustering to identify CRC-specific transcriptome subtypes in bulkseq, and rigorous quality controls, including the exclusion of cells with high mitochondrial gene expression in scRNA seq. Advanced analyses such as AUCcell, infercnvCNV, Non-negative Matrix Factorization (NMF), and CytoTRACE were utilized to dissect the cellular landscape and evaluate pathway activities and tumor cell stemness. The hdWGCNA algorithm helped identify prognosis-related hub genes, integrating these findings using a random forest machine learning model. Results: Kaplan-Meier survival curves identified 21 significant metabolic pathways linked to prognosis, with consensus clustering defining three CRC subtypes (C3, C2, C1) based on metabolic activity, which correlated with distinct clinical outcomes. The metabolic activity of the 13 cell subpopulations, particularly the epithelial cell subpopulation with active metabolic levels, was evaluated using AUCcell in scRNA seq. To further analyze tumor cells using infercnv, NMF disaggregated these cells into 10 cellular subpopulations. Among these, the C2 subpopulation exhibited higher stemness and tended to have a poorer prognosis compared to C6 and C0. Conversely, the C8, C3, and C1 subpopulations demonstrated a higher level of the five metabolic pathways, and the C3 and C8 subpopulations tended to have a more favorable prognosis. hdWGCNA identified 20 modules, from which we selected modules primarily expressed in high metabolic tumor subgroups and highly correlated with clinical information, including blue and cyan. By applying variable downscaling of RF to a total of 50 hub genes, seven gene signatures were obtained. Furthermore, molecules that were validated to be protective in GEO were screened alongside related molecules, resulting in the identification of prognostically relevant molecules such as UQCRFS1 and GRSF1. Additionally, the expression of GRSF1 was examined in colon cancer cell lines using qPCR and phenotypically verified by in vitro experiments. Conclusion: Our findings emphasize that high activity in specific metabolic pathways, including pyruvate metabolism and the tricarboxylic acid cycle, correlates with improved colon cancer outcomes, presenting new avenues for metabolic-based therapies. The identification of hub genes like GRSF1 and UQCRFS1 and their link to favorable metabolic profiles offers novel insights into tumor neovascularization and metastasis, with significant clinical implications for targeting metabolic pathways in CRC therapy.

A hybrid epithelial/mesenchymal state in head and neck cancer: A biomarker for survival with differential prognosis by self-reported race.

BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) is the 6th leading cause of cancer-related mortality, with racial disparities amplifying the challenges in treatment. Although the relationship between hybrid epithelial/mesenchymal (E/M) states and tumor progression is of interest, no studies have characterized the clinical relevance of hybrid E/M states in head and neck cancer outcomes among self-reported racial cohorts. METHODS: Given the overlap in gene expression between hybrid E/M malignant cells and cancer-associated fibroblasts, we utilized deconvolution of bulk RNA sequencing data from oral cavity and laryngeal squamous cell carcinoma tumors from The Cancer Genome Atlas. We utilized our previously collected single-cell profiles to generate inferred malignant profiles and then scored these for hybrid E/M. We then conducted a survival analysis on overall and disease-free survival among self-reported Black and White Americans. FINDINGS: The hybrid E/M state was differentially associated with head and neck cancer survival by self-reported race and ethnicity, with a stronger association in non-Hispanic Black patients. Black patients with a high hybrid E/M score had a higher risk of death or recurrence (hazard ratio [HR]: 4.18 [95% confidence interval (CI): 2.06, 8.49]) than White patients with a high hybrid E/M score (HR: 1.58 [95% CI: 1.11, 2.26]). CONCLUSION: Our results suggest a complex interplay of social structure, racism, and genetic diversity. We implore researchers to consider the social and biological context contributing to disparities. FUNDING: A.L.M. received support from the National Institute of Minority Health and Health Disparities (K01MD013897 [principal investigator (PI), A.L.M.]). S.V.P. received support from the National Institute of Dental and Craniofacial Research (R01DE032865 [PI, S.V.P.] and R01DE032371 [PI, S.V.P.]).

Genetic Prognostic Factors in Adult Diffuse Gliomas: A 10-Year Experience at a Single Institution.

Gliomas are primary brain lesions involving cerebral structures without well-defined boundaries and constitute the most prevalent central nervous system (CNS) neoplasms. Among gliomas, glioblastoma (GB) is a glioma of the highest grade and is associated with a grim prognosis. We examined how clinical variables and molecular profiles may have affected overall survival (OS) over the past ten years. A retrospective study was conducted at Sina Hospital in Tehran, Iran and examined patients with confirmed glioma diagnoses between 2012 and 2020. We evaluated the correlation between OS in GB patients and sociodemographic as well as clinical factors and molecular profiling based on IDH1, O-6-Methylguanine-DNA Methyltransferase (MGMT), TERTp, and epidermal growth factor receptor (EGFR) amplification (EGFR-amp) status. Kaplan-Meier and multivariate Cox regression models were used to assess patient survival. A total of 178 patients were enrolled in the study. The median OS was 20 months, with a 2-year survival rate of 61.0%. Among the 127 patients with available IDH measurements, 100 (78.7%) exhibited mutated IDH1 (IDH1-mut) tumors. Of the 127 patients with assessed MGMT promoter methylation (MGMTp-met), 89 (70.1%) had MGMT methylated tumors. Mutant TERTp (TERTp-mut) was detected in 20 out of 127 cases (15.7%), while wildtype TERTp (wildtype TERTp-wt) was observed in 107 cases (84.3%). Analyses using multivariable models revealed that age at histological grade (p < 0.0001), adjuvant radiotherapy (p < 0.018), IDH1 status (p < 0.043), and TERT-p status (p < 0.014) were independently associated with OS. Our study demonstrates that patients with higher tumor histological grades who had received adjuvant radiotherapy exhibited IDH1-mut or presented with TERTp-wt experienced improved OS. Besides, an interesting finding showed an association between methylation of MGMTp and TERTp status with tumor location.

KR158 Spheres Harboring Slow-Cycling Cells Recapitulate High-Grade Glioma Features in an Immunocompetent System.

Glioblastoma (GBM) poses a significant challenge in clinical oncology due to its aggressive nature, heterogeneity, and resistance to therapies. Cancer stem cells (CSCs) play a critical role in GBM, particularly in treatment resistance and tumor relapse, emphasizing the need to comprehend the mechanisms regulating these cells. Also, their multifaceted contributions to the tumor microenvironment (TME) underline their significance, driven by their unique properties. This study aimed to characterize glioblastoma stem cells (GSCs), specifically slow-cycling cells (SCCs), in an immunocompetent murine GBM model to explore their similarities with their human counterparts. Using the KR158 mouse model, we confirmed that SCCs isolated from this model exhibited key traits and functional properties akin to human SCCs. KR158 murine SCCs, expanded in the gliomasphere assay, demonstrated sphere forming ability, self-renewing capacity, positive tumorigenicity, enhanced stemness and resistance to chemotherapy. Together, our findings validate the KR158 murine model as a framework to investigate GSCs and SCCs in GBM pathology, and explore specifically the SCC-immune system communications, understand their role in disease progression, and evaluate the effect of therapeutic strategies targeting these specific connections.

Molecular insights to therapeutic in cancer: role of exosomes in tumor microenvironment, metastatic progression and drug resistance.

Exosomes play a pivotal part in cancer progression and metastasis by transferring various biomolecules. Recent research highlights their involvement in tumor microenvironment remodeling, mediating metastasis, tumor heterogeneity and drug resistance. The unique cargo carried by exosomes garners the interest of researchers owing to its potential as a stage-specific biomarker for early cancer detection and its role in monitoring personalized treatment. However, unanswered questions hinder a comprehensive understanding of exosomes and their cargo in this context. This review discusses recent advancements and proposes novel ideas for exploring exosomes in cancer progression, aiming to deepen our understanding and improve treatment approaches.

Human-derived Tumor-On-Chip model to study the heterogeneity of breast cancer tissue.

One of the leading causes that complicate the treatment of some malignancies, including breast cancer, is tumor heterogeneity. In addition to inter-heterogeneity and intra-heterogeneity of tumors that reflect the differences between cancer cell characteristics, heterogeneity in the tumor microenvironment plays a critical role in tumor progression and could be considered an overlooked and a proper target for the effective selection of therapeutic approaches. Due to the difficulty of completely capturing tumor heterogeneity in conventional detection methods, Tumor-on-Chip (TOC) devices with culturing patient-derived spheroids could be an appropriate alternative. In this research, human-derived spheroids from breast cancer individuals were cultured for 6 days in microfluidic devices. To compare TOC data with conventional detection methods, immunohistochemistry (IHC) and ITRAQ data were employed, and various protein expressions were validated using the transcriptomic databases. The behavior of the spheroids in the collagen matrix and the cell viability were monitored over 6 days of culture. IHC and immunocytochemistry (ICC) results revealed that inter and intra-heterogeneity of tumor spheroids are associated with HER2/ER expression. HER2 expression levels revealed a more important biomarker associated with invasion in the 3D culturing of spheroids. The expression levels of CD163 (as a marker for Ma2 macrophages) and CD44 (a marker for cancer stem cells (CSCs)) were also evaluated. Interestingly, the levels of M2a macrophages and CSCs were higher in triple-negative specimens and samples that showed higher migration and invasion. Cell density and extracellular matrix (ECM) stiffness were also important factors affecting the migration and invasion of the spheroids through the matrix. Among these, rigid ECM revealed a more crucial role than cell density. To sum up, these research findings demonstrated that human-derived spheroids from breast cancer specimens in microfluidic devices provide a dynamic condition for predicting tumor heterogeneity in patients, which can help move the field forward for better and more accurate therapeutic strategies.

A developmental constraint model of cancer cell states and tumor heterogeneity.

Cancer is a disease that stems from a fundamental liability inherent to multicellular life forms in which an individual cell is capable of reneging on the interests of the collective organism. Although cancer is commonly described as an evolutionary process, a less appreciated aspect of tumorigenesis may be the constraints imposed by the organism's developmental programs. Recent work from single-cell transcriptomic analyses across a range of cancer types has revealed the recurrence, plasticity, and co-option of distinct cellular states among cancer cell populations. Here, we note that across diverse cancer types, the observed cell states are proximate within the developmental hierarchy of the cell of origin. We thus posit a model by which cancer cell states are directly constrained by the organism's "developmental map." According to this model, a population of cancer cells traverses the developmental map, thereby generating a heterogeneous set of states whose interactions underpin emergent tumor behavior.

The value of whole tumor apparent diffusion coefficient histogram parameters in predicting meningiomas progesterone receptor expression.

This letter provides a critical assessment of a previous study on the utility of whole tumor apparent diffusion coefficient (ADC) histogram characteristics in predicting meningioma progesterone receptor expression. While acknowledging the benefits of employing classical diffusion-weighted imaging (DWI) for non-invasive tumor evaluation, it also emphasizes significant drawbacks. Advanced imaging techniques such as diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) were not used in the study, which could have provided a more comprehensive understanding of tumor microstructure and heterogeneity. Furthermore, the inclusion of necrotic and cystic areas in ADC analysis may distort results due to their different diffusion properties. While focusing on first-order ADC histogram characteristics is useful, it ignores the potential insights gained from higher-order features and texture analysis. These limitations indicate that future research should combine improved imaging modalities with thorough analytical methodologies to increase the predictive value of imaging biomarkers for meningioma features and progesterone receptor expression.

MicroRNA 421 induces the formation of high-invasive cell subsets of ovarian cancer from low-invasive cell subsets mediated by exosomes by activating the PI3K/AKT pathway.

Intratumoral heterogeneity (ITH) results in treatment failure in ovarian cancer (OC). Exosomes are related to the formation of a heterogeneous tumor microenvironment, and microRNAs play a crucial role in the progression of OC. Therefore, we aimed to explore the effect of exosomes and microRNA 421 (miR-421), which is mediated by exosomes, on ITH and the diagnosis of OC. Exosomes derived from A2780 cells with the highest (AHC) or lowest (ALC) invasive/migratory capacity cells (AHE/ALE) were extracted by differential centrifugation. We conducted a series of experiments to verify the role of AHE and miR-421 in promoting the transformation of low-invasive cells to high-invasive cells by regulating the PI3K/AKT pathway, and we also measured the levels of CA125 in serum exosomes. The results of assays showed that the AHE and miR-421, mediated by exosomes, significantly increased the malignancy of ALC cells by activating the PI3K/AKT pathway. The expression of miR-421 was significantly increased in the serum exosomes derived from high-grade serous ovarian cancer (HGSOC) patients. Our findings indicate that MiR-421, mediated by exosomes, could induce the transformation of highly invasive cell subpopulations from subpopulations of OC cells with low invasive potential by activating the PI3K/AKT signaling pathway.

Unveiling novel cell clusters and biomarkers in glioblastoma and its peritumoral microenvironment at the single-cell perspective.

BACKGROUND: Glioblastoma (GBM) is a highly heterogeneous, recurrent and aggressively invasive primary malignant brain tumor. The heterogeneity of GBM results in poor targeted therapy. Therefore, the aim of this study is to depict the cellular landscape of GBM and its peritumor from a single-cell perspective. Discovering new cell subtypes and biomarkers, and providing a theoretical basis for precision therapy. METHODS: We collected 8 tissue samples from 4 GBM patients to perform 10 × single-cell transcriptome sequencing. Quality control and filtering of data by Seurat package for clustering. Inferring copy number variations to identify malignant cells via the infercnv package. Functional enrichment analysis was performed by GSVA and clusterProfiler packages. STRING database and Cytoscape software were used to construct protein interaction networks. Inferring transcription factors by pySCENIC. Building cell differentiation trajectories via the monocle package. To infer intercellular communication networks by CellPhoneDB software. RESULTS: We observed that the tumor microenvironment (TME) varies among different locations and different GBM patients. We identified a proliferative cluster of oligodendrocytes with high expression of mitochondrial genes. We also identified two clusters of myeloid cells, one primarily located in the peritumor exhibiting an M1 phenotype with elevated TNFAIP8L3 expression, and another in the tumor and peritumor showing a proliferative tendency towards an M2 phenotype with increased DTL expression. We identified XIST, KCNH7, SYT1 and DIAPH3 as potential factors associated with the proliferation of malignant cells in GBM. CONCLUSIONS: These biomarkers and cell clusters we discovered may serve as targets for treatment. Targeted drugs developed against these biomarkers and cell clusters may enhance treatment efficacy, optimize immune therapy strategies, and improve the response rates of GBM patients to immunotherapy. Our findings provide a theoretical basis for the development of individualized treatment and precision medicine for GBM, which may be used to improve the survival of GBM patients.

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.

Microenvironment shapes small-cell lung cancer neuroendocrine states and presents therapeutic opportunities.

Small-cell lung cancer (SCLC) is the most fatal form of lung cancer. Intratumoral heterogeneity, marked by neuroendocrine (NE) and non-neuroendocrine (non-NE) cell states, defines SCLC, but the cell-extrinsic drivers of SCLC plasticity are poorly understood. To map the landscape of SCLC tumor microenvironment (TME), we apply spatially resolved transcriptomics and quantitative mass spectrometry-based proteomics to metastatic SCLC tumors obtained via rapid autopsy. The phenotype and overall composition of non-malignant cells in the TME exhibit substantial variability, closely mirroring the tumor phenotype, suggesting TME-driven reprogramming of NE cell states. We identify cancer-associated fibroblasts (CAFs) as a crucial element of SCLC TME heterogeneity, contributing to immune exclusion, and predicting exceptionally poor prognosis. Our work provides a comprehensive map of SCLC tumor and TME ecosystems, emphasizing their pivotal role in SCLC's adaptable nature, opening possibilities for reprogramming the TME-tumor communications that shape SCLC tumor states.

Temporal and spatial heterogeneity of HER2 status in metastatic colorectal cancer.

BACKGROUND: HER2-targeted therapies have recently emerged as an option in the management of metastatic colorectal cancer (mCRC) overexpressing HER2. However, data regarding HER2 status in primary CRC and its corresponding liver metastases are limited, potentially influencing clinical decisions. Therefore, the aim of this study was to compare the HER2 status in primary CRC and paired liver metastases. METHODS: Patients with mCRC who were operated from their primary colorectal cancer and their corresponding synchronous or metachronous liver metastases, in the digestive surgery department of Besançon University Hospital, between April 1999 and October 2021, were included. Tissue microarrays were constructed from matched primary CRC and liver metastastic tissue samples. HER2 status was assessed by immunohistochemistry and in situ hybridization according to Valtorta's criteria. RESULTS: A series of 108 paired primary CRC and liver metastases, including a series of multiple liver metastases originating from the same patients (n = 24), were assessed. Among the primary CRC, 89 (82.4%), 17 (15.8%) and 2 (1.8%) cases were scored 0, 1 + and 2 + respectively. In liver metastases, 99 (91.7%), 7 (6.5%) and 2 (1.8%) were scored 0, 1 + and 2, respectively. Overall, there was a 19% discrepancy rate in HER2 status between primary CRC and metastases, which increased to 21% in cases with multiple synchronous or metachronous liver metastases in a given patient. No significant difference was found between metachronous and synchronous metastases regarding the HER2 status (p = 0.237). CONCLUSIONS: Our study highlights the temporal and spatial heterogeneity of HER2 status between primary CRC and corresponding liver metastases. These findings raise the question of a sequential evaluation of the HER2 status during disease progression, to provide the most suitable treatment strategy.