Tumour heterogeneity and metastasis at single-cell resolution

SATB1 mediated tumor colonization and β-catenin nuclear localization are associated with colorectal cancer progression

Colorectal cancer (CRC) is a malignancy with high incidence and poor prognosis. It is urgent to identify valuable biomarkers for early diagnosis and potent therapeutic targets. It has been reported that SATB1 is associated with the malignant progression in CRC. To explore the role of SATB1 in CRC progression and the underlying mechanism, we evaluated the expression of SATB1 in the paired CRC tissues with immunohistochemistry. The results showed that the expression of SATB1 in lymph node metastasis was higher than that in primary lesion, and that in distant organ metastasis was higher than that in primary lesion. The retrospective analysis showed that patients with high expression of SATB1 had a significantly worse prognosis than those with negative and moderate expression. In vitro experiments that employing SATB1 over-expressing and depleted CRC cell lines confirmed that SATB1 contributes to cell proliferation and colonization, while inhibiting cell motility. Furthermore, the tissue immunofluorescence assay, Co-IP and Western blot were conducted to reveal that SATB1 induced translocation of β-catenin and formed a protein complex with it in the nuclei. In conclusion, SATB1 mediated tumor colonization and β-catenin nuclear localization are associated with the malignant progression and poor prognosis of CRC.

Single-cell multi-omics in the study of digestive system cancers

Digestive system cancers are prevalent diseases with a high mortality rate, posing a significant threat to public health and economic burden. The diagnosis and treatment of digestive system cancer confront conventional cancer problems, such as tumor heterogeneity and drug resistance. Single-cell sequencing (SCS) emerged at times required and has developed from single-cell RNA-seq (scRNA-seq) to the single-cell multi-omics era represented by single-cell spatial transcriptomics (ST). This article comprehensively reviews the advances of single-cell omics technology in the study of digestive system tumors. While analyzing and summarizing the research cases, vital details on the sequencing platform, sample information, sampling method, and key findings are provided. Meanwhile, we summarize the commonly used SCS platforms and their features, as well as the advantages of multi-omics technologies in combination. Finally, the development trends and prospects of the application of single-cell multi-omics technology in digestive system cancer research are prospected.

Mechanisms of lymph node metastasis: An extracellular vesicle perspective

In several solid tumors such as breast cancer, prostate cancer, colorectal cancer or melanoma, tumor draining lymph nodes are the earliest tissues where colonization by tumor cells is detected. Lymph nodes act as sentinels of metastatic dissemination, the deadliest phase of tumor progression. Besides hematogenous dissemination, lymphatic spread of tumor cells has been demonstrated, adding more complexity to the mechanisms involved in metastasis. A network of blood and lymphatic vessels surrounds tumors providing routes for tumor soluble factors to mediate regional and long-distance effects. Additionally, extracellular vesicles (EVs), particularly small EVs/exosomes, have been shown to circulate through the blood and lymph, favoring the formation of pre-metastatic niches in the tumor-draining lymph nodes (TDLNs) and distant organs. In this review, we present an overview of the relevance of lymph node metastasis, the structural and immune changes occurring in TDLNs during tumor progression, and how extracellular vesicles contribute to modulating some of these alterations while promoting the formation of lymph node pre-metastatic niches.

Natural and revolutionary tumor-specific T-cell therapy

Recently the FDA conducted a risk investigation and labeled the Boxed Warning for all BCMA- and CD19-directed CAR-T cell therapy, so does it mean that the public must take risk of secondary cancer to receive cell therapy? Here, without lentivirus and professional antigen presenting cell application, a novel tumor-specific T-cell therapy was successfully developed only by co-culturing MHC+ cancer cells and Naïve-T cells under the CD28 co-stimulatory signals. These tumor-specific T-cells could be separated through cell size and abundantly produced from peripheral blood, and would spontaneously attack target cells that carrying the same tumor antigen while avoiding others in vitro test. Moreover, it markedly decreased 90% tumor nodules companying with greatly improving overall survival (76 days vs 30 days) after twice infusion back to mice. This work maximally avoided the risks of secondary cancer and non-specific killing, and might open a revolutionary beginning of natural tumor-specific T-cell therapy.

Unlocking the potential: Targeting metabolic pathways in the tumor microenvironment for Cancer therapy

Cancer incidence and mortality are increasing and impacting global life expectancy. Metabolic reprogramming in the tumor microenvironment (TME) is intimately related to tumorigenesis, progression, metastasis and drug resistance. Tumor cells drive metabolic reprogramming of other cells in the TME through metabolic induction of cytokines and metabolites, and metabolic substrate competition. Consequently, this boosts tumor cell growth by providing metabolic support and facilitating immunosuppression and angiogenesis. The metabolic interplay in the TME presents potential therapeutic targets. Here, we focus on the metabolic reprogramming of four principal cell subsets in the TME: CAFs, TAMs, TILs and TECs, and their interaction with tumor cells. We also summarize medications and therapies targeting these cells' metabolic pathways, particularly in the context of immune checkpoint blockade therapy.

Tumor Cell Stemness and Stromal Cell Features Contribute to Oral Cancer Outcome Disparity in Black Americans

Black Americans (BAs) with head and neck cancer (HNC) have worse survival outcomes compared to the White patients. While HNC disparities in patient outcomes for BAs have been well recognized, the specific drivers of the inferior outcomes remain poorly understood. Here, we investigated the biologic features of patient tumor specimens obtained during the surgical treatment of oral cancers and performed a follow-up study of the patients' post-surgery recurrences and metastases with the aim to explore whether tumor biologic features could be associated with the poorer outcomes among BA patients compared with White American (WA) patients. We examined the tumor stemness traits and stromal properties as well as the post-surgery recurrence and metastasis of oral cancers among BA and WA patients. It was found that high levels of tumor self-renewal, invasion, tumorigenesis, metastasis, and tumor-promoting stromal characteristics were linked to post-surgery recurrence and metastasis. There were more BA than WA patients demonstrating high stemness traits and strong tumor-promoting stromal features in association with post-surgery tumor recurrences and metastases, although the investigated cases displayed clinically comparable TNM stages and histological grades. These findings demonstrated that the differences in tumor stemness and stromal property among cancers with comparable clinical diagnoses contribute to the outcome disparity in HNCs. More research is needed to understand the genetic and molecular basis of the biologic characteristics underlying the inferior outcomes among BA patients, so that targeting strategies can be developed to reduce HNC disparity.

Multi-omics evaluation of the prognostic value and immune signature of FCN1 in pan-cancer and its relationship with proliferation and apoptosis in acute myeloid leukemia

Background

The FCN1 gene encodes the ficolin-1 protein, implicated in the pathogenesis of various diseases, though its precise role in tumorigenesis remains elusive. This study aims to elucidate the prognostic significance, immune signature, and treatment response associated with FCN1 across diverse cancer types.

Methods

Employing multi-omics data, we conducted a comprehensive assessment, encompassing tissue-specific and single-cell-specific expression disparities, pan-cancer expression patterns, epigenetic modifications affecting FCN1 expression, and the immune microenvironment. Our investigation primarily focused on the clinical prognostic attributes, immune profiles, potential molecular mechanisms, and candidate therapeutic agents concerning FCN1 and acute myeloid leukemia (AML). Additionally, in vitro experiments were performed to scrutinize the impact of FCN1 knockdown on cell proliferation, apoptosis, and cell cycle dynamics within the AML cell line U937 and NB4.

Results

FCN1 expression exhibits widespread dysregulation across various cancers. Through both univariate and multivariate Cox regression analyses, FCN1 has been identified as an independent prognostic indicator for AML. Immunological investigations elucidate FCN1's involvement in modulating inflammatory responses within the tumor microenvironment and its correlation with treatment efficacy. Remarkably, the deletion of FCN1 influences the proliferation, apoptosis, and cell cycle dynamics of U937 cells and NB4 cells.

Conclusion

These findings underscore FCN1 as a promising pan-cancer biomarker indicative of macrophage infiltration, intimately linked with the tumor microenvironment and treatment responsiveness, and pivotal for cellular mechanisms within AML cell lines.

Open-ST: High-resolution spatial transcriptomics in 3D

Spatial transcriptomics (ST) methods unlock molecular mechanisms underlying tissue development, homeostasis, or disease. However, there is a need for easy-to-use, high-resolution, cost-efficient, and 3D-scalable methods. Here, we report Open-ST, a sequencing-based, open-source experimental and computational resource to address these challenges and to study the molecular organization of tissues in 2D and 3D. In mouse brain, Open-ST captured transcripts at subcellular resolution and reconstructed cell types. In primary head-and-neck tumors and patient-matched healthy/metastatic lymph nodes, Open-ST captured the diversity of immune, stromal, and tumor populations in space, validated by imaging-based ST. Distinct cell states were organized around cell-cell communication hotspots in the tumor but not the metastasis. Strikingly, the 3D reconstruction and multimodal analysis of the metastatic lymph node revealed spatially contiguous structures not visible in 2D and potential biomarkers precisely at the 3D tumor/lymph node boundary. All protocols and software are available at https://rajewsky-lab.github.io/openst.

Luciferase transduction and selection protocol for reliable in vivo bioluminescent measurements in cancer research

Bioluminescence imaging has become an essential non-invasive tool in cancer research for monitoring various cellular processes and tumor progression in vivo. In this article, we aimed to propose a transduction and selection protocol for reliable in vivo bioluminescent measurements in immunocompetent mouse models. Using two different heterogenous luciferase-expressing cell models, we underlined factors influencing transduction. The protocol was tested through an in vitro luciferase activity assay as well as using in vivo longitudinal monitoring of metastases formation (In Vivo Imaging System®). The data were cross validated with histological assessment. Our results demonstrated stable and proportional in vitro and in vivo bioluminescent signals correlating with actual metastatic burden. Furthermore, ex vivo analysis confirmed the accuracy of bioluminescent imaging in quantifying metastatic surface area. This protocol should ensure reliable and reproducible measurements in cancer research utilizing luciferase-positive cell lines, confirming the validity and accuracy of preclinical studies in immunocompetent models.

Tumor Subtype Classification Tool for HPV-associated Head and Neck Cancers

Importance

Molecular subtypes of HPV-associated Head and Neck Squamous Cell Carcinoma (HNSCC), named IMU (immune strong) and KRT (highly keratinized), are well-recognized and have been shown to have distinct mechanisms of carcinogenesis, clinical outcomes, and potentially differing optimal treatment strategies. Currently, no standardized method exists to subtype a new HPV+ HNSCC tumor. Our paper introduces a machine learning-based classifier and webtool to reliably subtype HPV+ HNSCC tumors using the IMU/KRT paradigm and highlights the importance of subtype in HPV+ HNSCC.

Objective

To develop a robust, accurate machine learning-based classification tool that standardizes the process of subtyping HPV+ HNSCC, and to investigate the clinical, demographic, and molecular features associated with subtype in a meta-analysis of four patient cohorts.

Data Sources

We conducted RNA-seq on 67 HNSCC FFPE blocks from University of Michigan hospital. Combining this with three publicly available datasets, we utilized a total of 229 HPV+ HNSCC RNA-seq samples. All participants were HPV+ according to RNA expression. An ensemble machine learning approach with five algorithms and three different input training gene sets were developed, with final subtype determined by majority vote. Several additional steps were taken to ensure rigor and reproducibility throughout.

Study Selection

The classifier was trained and tested using 84 subtype-labeled HPV+ RNA-seq samples from two cohorts: University of Michigan (UM; n=18) and TCGA-HNC (n=66). The classifier robustness was validated with two independent cohorts: 83 samples from the HPV Virome Consortium and 62 additional samples from UM. We revealed 24 of 39 tested clinicodemographic and molecular variables significantly associated with subtype.

Results

The classifier achieved 100% accuracy in the test set. Validation on two additional cohorts demonstrated successful separation by known features of the subtypes. Investigating the relationship between subtype and 39 molecular and clinicodemographic variables revealed IMU is associated with epithelial-mesenchymal transition (p=2.25×10-4), various immune cell types, and lower radiation resistance (p=0.0050), while KRT is more highly keratinized (p=2.53×10-8), and more likely female than IMU (p=0.0082).

Conclusions and Relevance

This study provides a reliable classifier for subtyping HPV+ HNSCC tumors as either IMU or KRT based on bulk RNA-seq data, and additionally, improves our understanding of the HPV+ HNSCC subtypes.

Are We There Yet? Assessing the Readiness of Single-Cell Proteomics to Answer Biological Hypotheses

Single-cell analysis is an active area of research in many fields of biology. Measurements at single-cell resolution allow researchers to study diverse populations without losing biologically meaningful information to sample averages. Many technologies have been used to study single cells, including mass spectrometry-based single-cell proteomics (SCP). SCP has seen a lot of growth over the past couple of years through improvements in data acquisition and analysis, leading to greater proteomic depth. Because method development has been the main focus in SCP, biological applications have been sprinkled in only as proof-of-concept. However, SCP methods now provide significant coverage of the proteome and have been implemented in many laboratories. Thus, a primary question to address in our community is whether the current state of technology is ready for widespread adoption for biological inquiry. In this Perspective, we examine the potential for SCP in three thematic areas of biological investigation: cell annotation, developmental trajectories, and spatial mapping. We identify that the primary limitation of SCP is sample throughput. As proteome depth has been the primary target for method development to date, we advocate for a change in focus to facilitate measuring tens of thousands of single-cell proteomes to enable biological applications beyond proof-of-concept.

Single-Cell RNA Sequencing: Technological Progress and Biomedical Application in Cancer Research

Single-cell RNA-seq (scRNA-seq) is a revolutionary technology that allows for the genomic investigation of individual cells in a population, allowing for the discovery of unusual cells associated with cancer and metastasis. ScRNA-seq has been used to discover different types of cancers with poor prognosis and medication resistance such as lung cancer, breast cancer, ovarian cancer, and gastric cancer. Besides, scRNA-seq is a promising method that helps us comprehend the biological features and dynamics of cell development, as well as other disorders. This review gives a concise summary of current scRNA-seq technology. We also explain the main technological steps involved in implementing the technology. We highlight the present applications of scRNA-seq in cancer research, including tumor heterogeneity analysis in lung cancer, breast cancer, and ovarian cancer. In addition, this review elucidates potential applications of scRNA-seq in lineage tracing, personalized medicine, illness prediction, and disease diagnosis, which reveals that scRNA-seq facilitates these events by producing genetic variations on the single-cell level.

Targeting Tumor Heterogeneity by Breaking a Stem Cell and Epithelial Niche Interaction Loop

Tumor heterogeneity, the presence of multiple distinct subpopulations of cancer cells between patients or among the same tumors, poses a major challenge to current targeted therapies. The way these different subpopulations interact among themselves and the stromal niche environment, and how such interactions affect cancer stem cell behavior has remained largely unknown. Here, it is shown that an FGF-BMP7-INHBA signaling positive feedback loop integrates interactions among different cell populations, including mammary gland stem cells, luminal epithelial and stromal fibroblast niche components not only in organ regeneration but also, with certain modifications, in cancer progression. The reciprocal dependence of basal stem cells and luminal epithelium is based on basal-derived BMP7 and luminal-derived INHBA, which promote their respective expansion, and is regulated by stromal-epithelial FGF signaling. Targeting this interaction loop, for example, by reducing the function of one or more of its components, inhibits organ regeneration and breast cancer progression. The results have profound implications for overcoming drug resistance because of tumor heterogeneity in future targeted therapies.

TNBC response to paclitaxel phenocopies interferon response which reveals cell cycle-associated resistance mechanisms

Paclitaxel is a standard of care neoadjuvant therapy for patients with triple negative breast cancer (TNBC); however, it shows limited benefit for locally advanced or metastatic disease. Here we used a coordinated experimental-computational approach to explore the influence of paclitaxel on the cellular and molecular responses of TNBC cells. We found that escalating doses of paclitaxel resulted in multinucleation, promotion of senescence, and initiation of DNA damage induced apoptosis. Single-cell RNA sequencing (scRNA-seq) of TNBC cells after paclitaxel treatment revealed upregulation of innate immune programs canonically associated with interferon response and downregulation of cell cycle progression programs. Systematic exploration of transcriptional responses to paclitaxel and cancer-associated microenvironmental factors revealed common gene programs induced by paclitaxel, IFNB, and IFNG. Transcription factor (TF) enrichment analysis identified 13 TFs that were both enriched based on activity of downstream targets and also significantly upregulated after paclitaxel treatment. Functional assessment with siRNA knockdown confirmed that the TFs FOSL1, NFE2L2 and ELF3 mediate cellular proliferation and also regulate nuclear structure. We further explored the influence of these TFs on paclitaxel-induced cell cycle behavior via live cell imaging, which revealed altered progression rates through G1, S/G2 and M phases. We found that ELF3 knockdown synergized with paclitaxel treatment to lock cells in a G1 state and prevent cell cycle progression. Analysis of publicly available breast cancer patient data showed that high ELF3 expression was associated with poor prognosis and enrichment programs associated with cell cycle progression. Together these analyses disentangle the diverse aspects of paclitaxel response and identify ELF3 upregulation as a putative biomarker of paclitaxel resistance in TNBC.

Research autopsy programmes in oncology: shared experience from 14 centres across the world

While there is a great clinical need to understand the biology of metastatic cancer in order to treat it more effectively, research is hampered by limited sample availability. Research autopsy programmes can crucially advance the field through synchronous, extensive, and high-volume sample collection. However, it remains an underused strategy in translational research. Via an extensive questionnaire, we collected information on the study design, enrolment strategy, study conduct, sample and data management, and challenges and opportunities of research autopsy programmes in oncology worldwide. Fourteen programmes participated in this study. Eight programmes operated 24 h/7 days, resulting in a lower median postmortem interval (time between death and start of the autopsy, 4 h) compared with those operating during working hours (9 h). Most programmes (n = 10) succeeded in collecting all samples within a median of 12 h after death. A large number of tumour sites were sampled during each autopsy (median 15.5 per patient). The median number of samples collected per patient was 58, including different processing methods for tumour samples but also non-tumour tissues and liquid biopsies. Unique biological insights derived from these samples included metastatic progression, treatment resistance, disease heterogeneity, tumour dormancy, interactions with the tumour micro-environment, and tumour representation in liquid biopsies. Tumour patient-derived xenograft (PDX) or organoid (PDO) models were additionally established, allowing for drug discovery and treatment sensitivity assays. Apart from the opportunities and achievements, we also present the challenges related with postmortem sample collections and strategies to overcome them, based on the shared experience of these 14 programmes. Through this work, we hope to increase the transparency of postmortem tissue donation, to encourage and aid the creation of new programmes, and to foster collaborations on these unique sample collections. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Histopathology Based AI Model Predicts Anti-Angiogenic Therapy Response in Renal Cancer Clinical Trial

Background

Predictive biomarkers of treatment response are lacking for metastatic clearcell renal cell carcinoma (ccRCC), a tumor type that is treated with angiogenesis inhibitors, immune checkpoint inhibitors, mTOR inhibitors and a HIF2 inhibitor. The Angioscore, an RNA-based quantification of angiogenesis, is arguably the best candidate to predict anti-angiogenic (AA) response. However, the clinical adoption of transcriptomic assays faces several challenges including standardization, time delay, and high cost. Further, ccRCC tumors are highly heterogenous, and sampling multiple areas for sequencing is impractical.

Approach

Here we present a novel deep learning (DL) approach to predict the Angioscore from ubiquitous histopathology slides. In order to overcome the lack of interpretability, one of the biggest limitations of typical DL models, our model produces a visual vascular network which is the basis of the model's prediction. To test its reliability, we applied this model to multiple cohorts including a clinical trial dataset.

Results

Our model accurately predicts the RNA-based Angioscore on multiple independent cohorts (spearman correlations of 0.77 and 0.73). Further, the predictions help unravel meaningful biology such as association of angiogenesis with grade, stage, and driver mutation status. Finally, we find our model is able to predict response to AA therapy, in both a real-world cohort and the IMmotion150 clinical trial. The predictive power of our model vastly exceeds that of CD31, a marker of vasculature, and nearly rivals the performance (c-index 0.66 vs 0.67) of the ground truth RNA-based Angioscore at a fraction of the cost.

Conclusion

By providing a robust yet interpretable prediction of the Angioscore from histopathology slides alone, our approach offers insights into angiogenesis biology and AA treatment response.

Digital droplet PCR analysis of organoids generated from mouse mammary tumors demonstrates proof-of-concept capture of tumor heterogeneity

Breast cancer metastases exhibit many different genetic alterations, including copy number amplifications (CNA). CNA are genetic alterations that are increasingly becoming relevant to breast oncology clinical practice. Here we identify CNA in metastatic breast tumor samples using publicly available datasets and characterize their expression and function using a metastatic mouse model of breast cancer. Our findings demonstrate that our organoid generation can be implemented to study clinically relevant features that reflect the genetic heterogeneity of individual tumors.

Temporal Single Cell Analysis of Leukemia Microenvironment Identifies Taurine-Taurine Transporter Axis as a Key Regulator of Myeloid Leukemia

Signals from the microenvironment are known to be critical for development, sustaining adult stem cells, and for oncogenic progression. While candidate niche-driven signals that can promote cancer progression have been identified1-6, concerted efforts to comprehensively map microenvironmental ligands for cancer stem cell specific surface receptors have been lacking. Here, we use temporal single cell RNA-sequencing to identify molecular cues from the bone marrow stromal niche that engage leukemia stem cells (LSC) during oncogenic progression. We integrate these data with our RNA-seq analysis of human LSCs from distinct aggressive myeloid cancer subtypes and our CRISPR based in vivo LSC dependency map7 to develop a temporal receptor-ligand interactome essential for disease progression. These analyses identify the taurine transporter (TauT)-taurine axis as a critical dependency of myeloid malignancies. We show that taurine production is restricted to the osteolineage population during cancer initiation and expansion. Inhibiting taurine synthesis in osteolineage cells impairs LSC growth and survival. Our experiments with the TauT genetic loss of function murine model indicate that its loss significantly impairs the progression of aggressive myeloid leukemias in vivo by downregulating glycolysis. Further, TauT inhibition using a small molecule strongly impairs the growth and survival of patient derived myeloid leukemia cells. Finally, we show that TauT inhibition can synergize with the clinically approved oxidative phosphorylation inhibitor venetoclax8, 9 to block the growth of primary human leukemia cells. Given that aggressive myeloid leukemias continue to be refractory to current therapies and have poor prognosis, our work indicates targeting the taurine transporter may be of therapeutic significance. Collectively, our data establishes a temporal landscape of stromal signals during cancer progression and identifies taurine-taurine transporter signaling as an important new regulator of myeloid malignancies.

The intricate interplay between cancer stem cells and cell-of-origin of cancer: implications for therapeutic strategies

Background

Cancer stem cells (CSCs) have emerged as pivotal players in tumorigenesis, disease progression, and resistance to therapies.

Objective

This comprehensive review delves into the intricate relationship between CSCs and the cell-of-origin in diverse cancer types.

Design

Comprehensive review of thematically-relevant literature.

Methods

We explore the underlying molecular mechanisms that drive the conversion of normal cells into CSCs and the impact of the cell-of-origin on CSC properties, tumor initiation, and therapeutic responses. Moreover, we discuss potential therapeutic interventions targeting CSCs based on their distinct cell-of-origin characteristics.

Results

Accruing evidence suggest that the cell-of-origin, the cell type from which the tumor originates, plays a crucial role in determining the properties of CSCs and their contribution to tumor heterogeneity.

Conclusion

By providing critical insights into the complex interplay between CSCs and their cellular origins, this article aims to enhance our understanding of cancer biology and pave the way for more effective and personalized cancer treatments.

Distinct molecular profiles drive multifaceted characteristics of colorectal cancer metastatic seeds

Metastasis of primary tumors remains a challenge for early diagnosis and prevention. The cellular properties and molecular drivers of metastatically competent clones within primary tumors remain unclear. Here, we generated 10-16 single cell-derived lines from each of three colorectal cancer (CRC) tumors to identify and characterize metastatic seeds. We found that intrinsic factors conferred clones with distinct metastatic potential and cellular communication capabilities, determining organ-specific metastasis. Poorly differentiated or highly metastatic clones, rather than drug-resistant clones, exhibited poor clinical prognostic impact. Personalized genetic alterations, instead of mutation burden, determined the occurrence of metastatic potential during clonal evolution. Additionally, we developed a gene signature for capturing metastatic potential of primary CRC tumors and demonstrated a strategy for identifying metastatic drivers using isogenic clones with distinct metastatic potential in primary tumors. This study provides insight into the origin and mechanisms of metastasis and will help develop potential anti-metastatic therapeutic targets for CRC patients.

Multiple RNA Rapid In Situ Imaging Based on Cas9 Code Key System

Existing RNA in situ imaging strategies mostly utilize parallel repetitive nucleic acid self-assembly to achieve multiple analysis, with limitations of complicated systems and cumbersome steps. Here, a Cas9 code key system with key probe (KP) encoder and CRISPR/Cas9 signal exporter is developed. This system triggers T-protospacer adjacent motif (T-PAM structural transitions of multiple KP encoders to form coding products with uniform single-guide RNA (sgRNA) target sequences as tandem nodes. Only single sgRNA/Cas9 complex is required to cleave multiple coding products, enabling efficient "many-to-one" tandem signaling, and non-collateral cleavage activity-dependent automatic signaling output through active introduction of mismatched bases. Compared with conventional parallel multiple signaling analysis model, the proposed system greatly simplifies reaction process and enhances detection efficiency. Further, a rapid multiple RNA in situ imaging system is developed by combining the Cas9 code key system with a T-strand displacement amplification (T-SDA) signal amplifier. The constructed system is applied to tumor cells and clinicopathology slices, generating clear multi-mRNA imaging profiles in less than an hour with just one step. Therefore, this work provides reliable technical support for clinical tumor typing and molecular mechanism investigation.

How CRISPR Is Revolutionizing the Generation of New Models for Cancer Research

Cancers arise through acquisition of mutations in genes that regulate core biological processes like cell proliferation and cell death. Decades of cancer research have led to the identification of genes and mutations causally involved in disease development and evolution, yet defining their precise function across different cancer types and how they influence therapy responses has been challenging. Mouse models have helped define the in vivo function of cancer-associated alterations, and genome-editing approaches using CRISPR have dramatically accelerated the pace at which these models are developed and studied. Here, we highlight how CRISPR technologies have impacted the development and use of mouse models for cancer research and discuss the many ways in which these rapidly evolving platforms will continue to transform our understanding of this disease.

Nuclear Softness Promotes the Metastatic Potential of Large-Nucleated Colorectal Cancer Cells via the ErbB4-Akt1-Lamin A/C Signaling Pathway

Abnormal nuclear enlargement is a diagnostic and physical hallmark of malignant tumors. Large nuclei are positively associated with an increased risk of developing metastasis; however, a large nucleus is inevitably more resistant to cell migration due to its size. The present study demonstrated that the nuclear size of primary colorectal cancer (CRC) cells at an advanced stage was larger than cells at an early stage. In addition, the nuclei of CRC liver metastases were larger than those of the corresponding primary CRC tissues. CRC cells were sorted into large-nucleated cells (LNCs) and small-nucleated cells (SNCs). Purified LNCs exhibited greater constricted migratory and metastatic capacity than SNCs in vitro and in vivo. Mechanistically, ErbB4 was highly expressed in LNCs, which phosphorylated lamin A/C at serine 22 via the ErbB4-Akt1 signaling pathway. Furthermore, the level of phosphorylated lamin A/C was a negative determinant of nuclear stiffness. Taken together, CRC LNCs possessed greater constricted migratory and metastatic potential than SNCs due to ErbB4-Akt1-mediated lamin A/C phosphorylation and nuclear softening. These results may provide a potential treatment strategy for tumor metastasis by targeting nuclear stiffness in patients with cancer, particularly CRC.

GATA4 regulates the transcription of MMP9 to suppress the invasion and migration of breast cancer cells via HDAC1-mediated p65 deacetylation

GATA-binding protein 4 (GATA4) is recognized for its significant roles in embryogenesis and various cancers. Through bioinformatics and clinical data, it appears that GATA4 plays a role in breast cancer development. Yet, the specific roles and mechanisms of GATA4 in breast cancer progression remain elusive. In this study, we identify GATA4 as a tumor suppressor in the invasion and migration of breast cancer. Functionally, GATA4 significantly reduces the transcription of MMP9. On a mechanistic level, GATA4 diminishes MMP9 transcription by interacting with p65 at the NF-κB binding site on the MMP9 promoter. Additionally, GATA4 promotes the recruitment of HDAC1, amplifying the bond between p65 and HDAC1. This leads to decreased acetylation of p65, thus inhibiting p65's transcriptional activity on the MMP9 promoter. Moreover, GATA4 hampers the metastasis of breast cancer in vivo mouse model. In summary, our research unveils a novel mechanism wherein GATA4 curtails breast cancer cell metastasis by downregulating MMP9 expression, suggesting a potential therapeutic avenue for breast cancer metastasis.

scGAL: unmask tumor clonal substructure by jointly analyzing independent single-cell copy number and scRNA-seq data

BACKGROUND

Accurately deciphering clonal copy number substructure can provide insights into the evolutionary mechanism of cancer, and clustering single-cell copy number profiles has become an effective means to unmask intra-tumor heterogeneity (ITH). However, copy numbers inferred from single-cell DNA sequencing (scDNA-seq) data are error-prone due to technically confounding factors such as amplification bias and allele-dropout, and this makes it difficult to precisely identify the ITH.

RESULTS

We introduce a hybrid model called scGAL to infer clonal copy number substructure. It combines an autoencoder with a generative adversarial network to jointly analyze independent single-cell copy number profiles and gene expression data from same cell line. Under an adversarial learning framework, scGAL exploits complementary information from gene expression data to relieve the effects of noise in copy number data, and learns latent representations of scDNA-seq cells for accurate inference of the ITH. Evaluation results on three real cancer datasets suggest scGAL is able to accurately infer clonal architecture and surpasses other similar methods. In addition, assessment of scGAL on various simulated datasets demonstrates its high robustness against the changes of data size and distribution. scGAL can be accessed at: https://github.com/zhyu-lab/scgal .

CONCLUSIONS

Joint analysis of independent single-cell copy number and gene expression data from a same cell line can effectively exploit complementary information from individual omics, and thus gives more refined indication of clonal copy number substructure.

Cuproptosis/OXPHOS tendency prediction of prognosis and immune microenvironment of esophageal squamous cell carcinoma: Bioinformatics analysis and experimental validation

BACKGROUND

Cuproptosis is a newly discovered cell death mechanism that relies on mitochondrial respiration, for which oxidative phosphorylation (OXPHOS) is an essential part. However, the detailed mechanisms of cuproptosis associated with OXPHOS in esophageal squamous cell carcinoma (ESCC) and how this correlation affects prognosis still remains unclear.

METHODS

scRNA-seq data of ESCC were downloaded from SRA (Sequence Read Archive) database. "AUCell" algorithm was used to grouping epithelial cells according to cuproptosis and OXPHOS score. Cell-cell communication, Pseudo-time Trajectory and transcription factor enrichment analysis were repectively conducted by "CellChat", "monocle3" package and "pySCENIC" algorithm. Univariate and LASSO cox regression analysis were used to construct the prognostic cuproptosis-OXPHOS signature. Finally, CCK-8 assay and DCFH-DA staining assay were respectively validated the sensitive and ROS production of elesclomol.

RESULTS

scRNA-seq data were analyzed to identify 10 core cell types. According to the median scores for cuproptosis and OXPHOS, malignant epithelial cells were divided into double high, double low, and mixed groups. The double high group distributed at the end of the pseudo-time trajectory and harbored HMGA1(+) as specific transcriptional regulons. Knockdown of HMGA1 partly reversed the inhibition of cell viability visualized by CCK-8 assay, while reactive oxygen species (ROS) production by elesclomol was enhanced after HMGA1 silencing. Furthermore, the immunosuppressive signal was significantly increased in the double high group detected by 'CellChat' in single-cell data and 'ssGSEA' in bulk data followed by 'CIBERSORTx' algorithm. Finally, a new cuproptosis-OXPHOS prognostic signature (CNN2, ATP6V0E1, PSMD6, CCDC25, IGFBP2, MT1E, and RPS4Y1) was constructed for the prediction of the prognosis, and a high-risk group corresponding to a more sensitive tendency to erlotinib, dasatinib, and bosutinib treatment was identified.

CONCLUSIONS

Our study revealed the relationship between OXPHOS and tendency of cuproptosis in ESCC, and malignant cells with this characteristic exerted immunosuppressive signals and indicated poor prognosis. Furthermore, we constructed the regulatory network in high cuproptosis-OXPHOS ESCC and identified HMGA1 as a potential regulator molecule of cuproptosis mediated by elesclomol.

Sprouty genes regulate activated fibroblasts in mammary epithelial development and breast cancer

Stromal fibroblasts are a major stem cell niche component essential for organ formation and cancer development. Fibroblast heterogeneity, as revealed by recent advances in single-cell techniques, has raised important questions about the origin, differentiation, and function of fibroblast subtypes. In this study, we show in mammary stromal fibroblasts that loss of the receptor tyrosine kinase (RTK) negative feedback regulators encoded by Spry1, Spry2, and Spry4 causes upregulation of signaling in multiple RTK pathways and increased extracellular matrix remodeling, resulting in accelerated epithelial branching. Single-cell transcriptomic analysis demonstrated that increased production of FGF10 due to Sprouty (Spry) loss results from expansion of a functionally distinct subgroup of fibroblasts with the most potent branching-promoting ability. Compared to their three independent lineage precursors, fibroblasts in this subgroup are "activated," as they are located immediately adjacent to the epithelium that is actively undergoing branching and invasion. Spry genes are downregulated, and activated fibroblasts are expanded, in all three of the major human breast cancer subtypes. Together, our data highlight the regulation of a functional subtype of mammary fibroblasts by Spry genes and their essential role in epithelial morphogenesis and cancer development.

GTADC: A Graph-Based Method for Inferring Cell Spatial Distribution in Cancer Tissues

The heterogeneity of tumors poses a challenge for understanding cell interactions and constructing complex ecosystems within cancer tissues. Current research strategies integrate spatial transcriptomics (ST) and single-cell sequencing (scRNA-seq) data to thoroughly analyze this intricate system. However, traditional deep learning methods using scRNA-seq data tend to filter differentially expressed genes through statistical methods. In the context of cancer tissues, where cancer cells exhibit significant differences in gene expression compared to normal cells, this heterogeneity renders traditional analysis methods incapable of accurately capturing differences between cell types. Therefore, we propose a graph-based deep learning method, GTADC, which utilizes Silhouette scores to precisely capture genes with significant expression differences within each cell type, enhancing the accuracy of gene selection. Compared to traditional methods, GTADC not only considers the expression similarity of genes within their respective clusters but also comprehensively leverages information from the overall clustering structure. The introduction of graph structure effectively captures spatial relationships and topological structures between the two types of data, enabling GTADC to more accurately and comprehensively resolve the spatial composition of different cell types within tissues. This refinement allows GTADC to intricately reconstruct the cellular spatial composition, offering a precise solution for inferring cell spatial composition. This method allows for early detection of potential cancer cell regions within tissues, assessing their quantity and spatial information in cell populations. We aim to achieve a preliminary estimation of cancer occurrence and development, contributing to a deeper understanding of early-stage cancer and providing potential support for early cancer diagnosis.

Xenograft and organoid models in developing precision medicine for gastric cancer (Review)

Gastric cancer (GC), a highly heterogeneous disease, has diverse histological and molecular subtypes. For precision medicine, well‑characterized models encompassing the full spectrum of subtypes are necessary. Patient‑derived tumor xenografts and organoids serve as important preclinical models in GC research. The main advantage of these models is the retention of phenotypic and genotypic heterogeneity present in parental tumor tissues. Utilizing diverse sequencing techniques and preclinical models for GC research facilitates accuracy in predicting personalized clinical responses to anti‑cancer treatments. The present review summarizes the latest advances of these two preclinical models in GC treatment and drug response assessment.

Histone 3 lysine 9 acetylation-specific reprogramming regulates esophageal squamous cell carcinoma progression and metastasis

Dysregulation of histone acetylation is widely implicated in tumorigenesis, yet its specific roles in the progression and metastasis of esophageal squamous cell carcinoma (ESCC) remain unclear. Here, we profiled the genome-wide landscapes of H3K9ac for paired adjacent normal (Nor), primary ESCC (EC) and metastatic lymph node (LNC) esophageal tissues from three ESCC patients. Compared to H3K27ac, we identified a distinct epigenetic reprogramming specific to H3K9ac in EC and LNC samples relative to Nor samples. This H3K9ac-related reprogramming contributed to the transcriptomic aberration of targeting genes, which were functionally associated with tumorigenesis and metastasis. Notably, genes with gained H3K9ac signals in both primary and metastatic lymph node samples (common-gained gene) were significantly enriched in oncogenes. Single-cell RNA-seq analysis further revealed that the corresponding top 15 common-gained genes preferred to be enriched in mesenchymal cells with high metastatic potential. Additionally, in vitro experiment demonstrated that the removal of H3K9ac from the common-gained gene MSI1 significantly downregulated its transcription, resulting in deficiencies in ESCC cell proliferation and migration. Together, our findings revealed the distinct characteristics of H3K9ac in esophageal squamous cell carcinogenesis and metastasis, and highlighted the potential therapeutic avenue for intervening ESCC through epigenetic modulation via H3K9ac.

Encapsulation and release of calcein from herceptin-conjugated eLiposomes

Achieving an optimal therapeutic level is crucial in effectively eradicating cancer cells during treatment. However, conventional chemotherapy-associated systemic administration of anticancer agents leads to many side effects. To achieve the desired control over the target site, active targeting of HER2-positive breast cancer cells can be achieved by conjugating liposomal vesicles with Human Epidermal growth factor Receptor 2 (HER2) and inducing release of the encapsulated drug using ultrasound. To further enhance the delivery efficiency, nanoemulsion droplets exhibiting responsiveness to low-frequency ultrasound are encapsulated within these lipid vesicles. In this study, we prepared four different liposomal formulations, namely pegylated liposomes, emulsion liposomes (eLiposomes), HER-conjugated liposomes, and HER-conjugated eLiposomes, each loaded with calcein and subjected to a thorough characterization process. Their sizes, phospholipid concentration, and amount of antibody conjugation were compared and analyzed. Cryogenic transmission electron microscopy was used to confirm the encapsulation of nanoemulsion droplets within the liposomes. The drug-releasing performance of Herceptin-conjugated eLiposomes was found to surpass that of other liposomal formulations with a notably higher calcein release and established it as a highly effective nanocarrier. The study showcases the efficacy of calcein-loaded and Herceptin-conjugated eLiposomes, which demonstrate rapid and efficient drug release among other liposomal formulations when subjected to ultrasound. This discovery paves the way for a more targeted, efficient, and humane approach to cancer therapy.

Exploring the metastasis-related biomarker and carcinogenic mechanism in liver cancer based on single cell technology

Background

Hepatocellular carcinoma (HCC) is a fatal primary malignancy characterized by high invasion and migration. We aimed to explore the underlying metastasis-related mechanism supporting the development of HCC.

Methods

The dataset of single cell RNA-seq (GSE149614) were collected for cell clustering by using the Seurat R package, the FindAllMarkers function was used to find the highly expression and defined the cell cluster. The WebGestaltR package was used for the GO and KEGG function analysis of shared genes, the Gene Set Enrichment Analysis (GSVA) was performed by clusterProfiler R package, the hTFtarget database was used to identify the crucial transcription factors (TFs), the Genomics of Drug Sensitivity in Cancer (GDSC) database was used for the drug sensitivity analysis. Finally, the overexpression and trans-well assay was used for gene function analysis.

Results

We obtained 9 cell clusters from the scRNA-seq data, including the nature killer (NK)/T cells, Myeloid cells, Hepatocytes, Epithelial cells, Endothelial cells, Plasma B cells, Smooth muscle cells, B cells, Liver bud hepatic cells. Further cell ecological analysis indicated that the Hepatocytes and Endothelial cell cluster were closely related to the cancer metastasis. Subsequently, the NDUFA4L2-Hepatocyte, GTSE1-Hepatocyte, ENTPD1-Endothelial and NDUFA4L2-Endothelial were defined as metastasis-supporting cell clusters, in which the NDUFA4L2-Hepatocyte cells was closely related to angiogenesis, while the NDUFA4L2-Endothelial was related with the inflammatory response and complement response. The overexpression and trans-well assay displayed that NDUFA4L2 exhibited clearly metastasis-promoting role in HCC progression.

Conclusion

We identified and defined 4 metastasis-supporting cell clusters by using the single cell technology, the specify shared gene was observed and played crucial role in promoting cancer progression, our findings were expected to provide new insight in control cancer metastasis.

Canopy2: tumor phylogeny inference by bulk DNA and single-cell RNA sequencing

Tumors are comprised of a mixture of distinct cell populations that differ in terms of genetic makeup and function. Such heterogeneity plays a role in the development of drug resistance and the ineffectiveness of targeted cancer therapies. Insight into this complexity can be obtained through the construction of a phylogenetic tree, which illustrates the evolutionary lineage of tumor cells as they acquire mutations over time. We propose Canopy2, a Bayesian framework that uses single nucleotide variants derived from bulk DNA and single-cell RNA sequencing to infer tumor phylogeny and conduct mutational profiling of tumor subpopulations. Canopy2 uses Markov chain Monte Carlo methods to sample from a joint probability distribution involving a mixture of binomial and beta-binomial distributions, specifically chosen to account for the sparsity and stochasticity of the single-cell data. Canopy2 demystifies the sources of zeros in the single-cell data and separates zeros categorized as non-cancerous (cells without mutations), stochastic (mutations not expressed due to bursting), and technical (expressed mutations not picked up by sequencing). Simulations demonstrate that Canopy2 consistently outperforms competing methods and reconstructs the clonal tree with high fidelity, even in situations involving low sequencing depth, poor single-cell yield, and highly-advanced and polyclonal tumors. We further assess the performance of Canopy2 through application to breast cancer and glioblastoma data, benchmarking against existing methods. Canopy2 is an open-source R package available at https://github.com/annweideman/canopy2.

Molecular perspectives on systemic priming and concomitant immunity in colorectal carcinoma

The progression of metastasis, a complex systemic disease, is facilitated by interactions between tumor cells and their isolated microenvironments. Over the past few decades, researchers have investigated the metastatic spread of cancer extensively, identifying multiple stages in the process, such as intravasation, extravasation, tumor latency, and the development of micrometastasis and macrometastasis. The premetastatic niche is established in target organs by the accumulation of aberrant immune cells and extracellular matrix proteins. The "seed and soil" idea, which has become widely known and accepted, is being used to this day to guide cancer studies. Changes in the local and systemic immune systems have a major impact on whether an infection spreads or not. The belief that the immune response may play a role in slowing tumor growth and may be beneficial against the metastatic disease underpins the responsiveness shown in the immunological landscape of metastasis. Various hypotheses on the phylogenesis of metastases have been proposed in the past. The primary tumor's secreting factors shape the intratumoral microenvironment and the immune landscape, allowing this progress to be made. Therefore, it is evident that among disseminated tumor cells, there are distinct phenotypes that either carry budding for metastasis or have the ability to obtain this potential or in systemic priming through contact with substantial metastatic niches that have implications for medicinal chemistry. Concurrent immunity signals that the main tumor induces an immune response that may not be strong enough to eradicate the tumor. Immunotherapy's success with some cancer patients shows that it is possible to effectively destroy even advanced-stage tumors by modifying the microenvironment and tumor-immune cell interactions. This review focuses on the metastasome in colorectal carcinoma and the therapeutic implications of site-specific metastasis, systemic priming, tumor spread, and the relationship between the immune system and metastasis.

Cellular heterogeneity in TNF/TNFR1 signalling: live cell imaging of cell fate decisions in single cells

Cellular responses to TNF are inherently heterogeneous within an isogenic cell population and across different cell types. TNF promotes cell survival by activating pro-inflammatory NF-κB and MAPK signalling pathways but may also trigger apoptosis and necroptosis. Following TNF stimulation, the fate of individual cells is governed by the balance of pro-survival and pro-apoptotic signalling pathways. To elucidate the molecular mechanisms driving heterogenous responses to TNF, quantifying TNF/TNFR1 signalling at the single-cell level is crucial. Fluorescence live-cell imaging techniques offer real-time, dynamic insights into molecular processes in single cells, allowing for detection of rapid and transient changes, as well as identification of subpopulations, that are likely to be missed with traditional endpoint assays. Whilst fluorescence live-cell imaging has been employed extensively to investigate TNF-induced inflammation and TNF-induced cell death, it has been underutilised in studying the role of TNF/TNFR1 signalling pathway crosstalk in guiding cell-fate decisions in single cells. Here, we outline the various opportunities for pathway crosstalk during TNF/TNFR1 signalling and how these interactions may govern heterogenous responses to TNF. We also advocate for the use of live-cell imaging techniques to elucidate the molecular processes driving cell-to-cell variability in single cells. Understanding and overcoming cellular heterogeneity in response to TNF and modulators of the TNF/TNFR1 signalling pathway could lead to the development of targeted therapies for various diseases associated with aberrant TNF/TNFR1 signalling, such as rheumatoid arthritis, metabolic syndrome, and cancer.

Multiplex protein imaging in tumour biology

Tissue imaging has become much more colourful in the past decade. Advances in both experimental and analytical methods now make it possible to image protein markers in tissue samples in high multiplex. The ability to routinely image 40-50 markers simultaneously, at single-cell or subcellular resolution, has opened up new vistas in the study of tumour biology. Cellular phenotypes, interaction, communication and spatial organization have become amenable to molecular-level analysis, and application to patient cohorts has identified clinically relevant cellular and tissue features in several cancer types. Here, we review the use of multiplex protein imaging methods to study tumour biology, discuss ongoing attempts to combine these approaches with other forms of spatial omics, and highlight challenges in the field.

Imaging-based characterization of tumoral heterogeneity for personalized cancer treatment

With personalized tumor therapy, understanding and addressing the heterogeneity of malignant tumors is becoming increasingly important. Heterogeneity can be found within one lesion (intralesional) and between several tumor lesions emerging from one primary tumor (interlesional). The heterogeneous tumor cells may show a different response to treatment due to their biology, which in turn influences the outcome of the affected patients and the choice of therapeutic agents. Therefore, both intra- and interlesional heterogeneity should be addressed at the diagnostic stage. While genetic and biological heterogeneity are important parameters in molecular tumor characterization and in histopathology, they are not yet addressed routinely in medical imaging. This article summarizes the recently established markers for tumor heterogeneity in imaging as well as heterogeneous/mixed response to therapy. Furthermore, a look at emerging markers is given. The ultimate goal of this overview is to provide comprehensive understanding of tumor heterogeneity and its implications for radiology and for communication with interdisciplinary teams in oncology. KEY POINTS::   · Tumor heterogeneity can be described within one lesion (intralesional) or between several lesions (interlesional).. · The heterogeneous biology of tumor cells can lead to a mixed therapeutic response and should be addressed in diagnostics and the therapeutic regime.. · Quantitative image diagnostics can be enhanced using AI, improved histopathological methods, and liquid profiling in the future..

Deciphering cellular plasticity in pancreatic cancer for effective treatments

Cellular plasticity and therapy resistance are critical features of pancreatic cancer, a highly aggressive and fatal disease. The pancreas, a vital organ that produces digestive enzymes and hormones, is often affected by two main types of cancer: the pre-dominant ductal adenocarcinoma and the less common neuroendocrine tumors. These cancers are difficult to treat due to their complex biology characterized by cellular plasticity leading to therapy resistance. Cellular plasticity refers to the capability of cancer cells to change and adapt to different microenvironments within the body which includes acinar-ductal metaplasia, epithelial to mesenchymal/epigenetic/metabolic plasticity, as well as stemness. This plasticity allows heterogeneity of cancer cells, metastasis, and evasion of host's immune system and develops resistance to radiation, chemotherapy, and targeted therapy. To overcome this resistance, extensive research is ongoing exploring the intrinsic and extrinsic factors through cellular reprogramming, chemosensitization, targeting metabolic, key survival pathways, etc. In this review, we discussed the mechanisms of cellular plasticity involving cellular adaptation and tumor microenvironment and provided a comprehensive understanding of its role in therapy resistance and ways to overcome it.

Applications of single-cell omics for chimeric antigen receptor T cell therapy

Chimeric antigen receptor (CAR) T cell therapy is a promising cancer treatment modality. The breakthroughs in CAR T cell therapy were, in part, possible with the help of cell analysis methods, such as single-cell analysis. Bulk analyses have provided invaluable information regarding the complex molecular dynamics of CAR T cells, but their results are an average of thousands of signals in CAR T or tumour cells. Since cancer is a heterogeneous disease where each minute detail of a subclone could change the outcome of the treatment, single-cell analysis could prove to be a powerful instrument in deciphering the secrets of tumour microenvironment for cancer immunotherapy. With the recent studies in all aspects of adoptive cell therapy making use of single-cell analysis, a comprehensive review of the recent preclinical and clinical findings in CAR T cell therapy was needed. Here, we categorized and summarized the key points of the studies in which single-cell analysis provided insights into the genomics, epigenomics, transcriptomics and proteomics as well as their respective multi-omics of CAR T cell therapy.

Recent advances in micro-physiological systems for investigating tumor metastasis and organotropism

Tumor metastasis involves complex processes that traditional 2D cultures and animal models struggle to fully replicate. Metastatic tumors undergo a multitude of transformations, including genetic diversification, adaptation to diverse microenvironments, and modified drug responses, contributing significantly to cancer-related mortality. Micro-physiological systems (MPS) technology emerges as a promising approach to emulate the metastatic process by integrating critical biochemical, biomechanical, and geometrical cues at a microscale. These systems are particularly advantageous simulating metastasis organotropism, the phenomenon where tumors exhibit a preference for metastasizing to particular organs. Organotropism is influenced by various factors, such as tumor cell characteristics, unique organ microenvironments, and organ-specific vascular conditions, all of which can be effectively examined using MPS. This review surveys the recent developments in MPS research from the past five years, with a specific focus on their applications in replicating tumor metastasis and organotropism. Furthermore, we discuss the current limitations in MPS-based studies of organotropism and propose strategies for more accurately replicating and analyzing the intricate aspects of organ-specific metastasis, which is pivotal in the development of targeted therapeutic approaches against metastatic cancers.

Lineage and ecology define liver tumor evolution in response to treatment

A tumor ecosystem constantly evolves over time in the face of immune predation or therapeutic intervention, resulting in treatment failure and tumor progression. Here, we present a single-cell transcriptome-based strategy to determine the evolution of longitudinal tumor biopsies from liver cancer patients by measuring cellular lineage and ecology. We construct a lineage and ecological score as joint dynamics of tumor cells and their microenvironments. Tumors may be classified into four main states in the lineage-ecological space, which are associated with clinical outcomes. Analysis of longitudinal samples reveals the evolutionary trajectory of tumors in response to treatment. We validate the lineage-ecology-based scoring system in predicting clinical outcomes using bulk transcriptomic data of additional cohorts of 716 liver cancer patients. Our study provides a framework for monitoring tumor evolution in response to therapeutic intervention.

Multimodal immune phenotyping reveals microbial-T cell interactions that shape pancreatic cancer

Microbes are an integral component of the tumor microenvironment. However, determinants of microbial presence remain ill-defined. Here, using spatial-profiling technologies, we show that bacterial and immune cell heterogeneity are spatially coupled. Mouse models of pancreatic cancer recapitulate the immune-microbial spatial coupling seen in humans. Distinct intra-tumoral niches are defined by T cells, with T cell-enriched and T cell-poor regions displaying unique bacterial communities that are associated with immunologically active and quiescent phenotypes, respectively, but are independent of the gut microbiome. Depletion of intra-tumoral bacteria slows tumor growth in T cell-poor tumors and alters the phenotype and presence of myeloid and B cells in T cell-enriched tumors but does not affect T cell infiltration. In contrast, T cell depletion disrupts the immunological state of tumors and reduces intra-tumoral bacteria. Our results establish a coupling between microbes and T cells in cancer wherein spatially defined immune-microbial communities differentially influence tumor biology.

Divergent iron-regulatory states contribute to heterogeneity in breast cancer aggressiveness

Primary tumors with similar mutational profiles can progress to vastly different outcomes where transcriptional state, rather than mutational profile, predicts prognosis. A key challenge is to understand how distinct tumor cell states are induced and maintained. In triple negative breast cancer cells, invasive behaviors and aggressive transcriptional signatures linked to poor patient prognosis can emerge in response to contact with collagen type I. Herein, collagen-induced migration heterogeneity within a TNBC cell line was leveraged to identify transcriptional programs associated with invasive versus non-invasive phenotypes and implicate molecular switches. Phenotype-guided sequencing revealed that invasive cells upregulate iron uptake and utilization machinery, anapleurotic TCA cycle genes, actin polymerization promoters, and a distinct signature of Rho GTPase activity and contractility regulating genes. The non-invasive cell state is characterized by actin and iron sequestration modules along with glycolysis gene expression. These unique tumor cell states are evident in patient tumors and predict divergent outcomes for TNBC patients. Glucose tracing confirmed that non-invasive cells are more glycolytic than invasive cells, and functional studies in cell lines and PDO models demonstrated a causal relationship between phenotype and metabolic state. Mechanistically, the OXPHOS dependent invasive state resulted from transient HO-1 upregulation triggered by contact with dense collagen that reduced heme levels and mitochondrial chelatable iron levels. This induced expression of low cytoplasmic iron response genes regulated by ACO1/IRP1. Knockdown or inhibition of HO-1, ACO1/IRP1, MRCK, or OXPHOS abrogated invasion. These findings support an emerging theory that heme and iron flux serve as important regulators of TNBC aggressiveness.

Non-mitotic proliferation of malignant cancer cells revealed through live-cell imaging of primary and cell-line cultures

INTRODUCTION

Anti-mitosis has been a key strategy of anti-cancer therapies, targeting at a fundamental property of cancer cells, their non-controllable proliferation due to overactive mitotic divisions. For improved anti-cancer therapies, it is important to find out whether cancer cells can proliferate independent of mitosis and become resistant to anti-mitotic agents.

RESULTS

In this study, live-cell imaging was applied to both primary-cultures of tumor cells, and immortalized cancer cell lines, to detect aberrant proliferations. Cells isolated from various malignant tumors, such as Grade-III hemangiopericytoma, atypical meningioma, and metastatic brain tumor exhibit distinct cellular behaviors, including amoeboid sequestration, tailing, tunneling, nucleic DNA leakage, as well as prokaryote-like division such as binary fission and budding-shedding, which are collectively referred to and reported as 'non-mitotic proliferation' in this study. In contrast, benign tumors including Grade-I hemangiopericytoma and meningioma were not obvious in such behaviors. Moreover, when cultured in medium free of any anti-cancer drugs, cells from a recurrent Grade-III hemangiopericytoma that had been subjected to pre-operation adjuvant chemotherapy gradually shifted from non-mitotic proliferation to abnormal mitosis in the form of daughter number variation (DNV) and endomitosis, and eventually regular mitosis. Similarly, when treated with the anti-cancer drugs Epirubicin or Cisplatin, the cancer cell lines HeLa and A549 showed a shift from regular mitosis to abnormal mitosis, and further to non-mitosis as the dominant mode of proliferation with increasing drug concentrations. Upon removal of the drugs, the cells reversed back to regular mitosis with only minor occurrences of abnormal mitosis, accompanied by increased expression of the stem cell markers ALDH1, Sox, Oct4 and Nanog.

CONCLUSIONS

The present study revealed that various types of malignant, but not benign, cancer cells exhibited cellular behaviors indicative of non-mitotic proliferation such as binary fission, which was typical of prokaryotic cell division, suggesting cell level atavism. Moreover, reversible transitions through the three modes of proliferation, i.e., mitosis, abnormal mitosis and non-mitosis, were observed when anticancer drug concentrations were grossly increased inducing non-mitosis or decreased favoring mitosis. Potential clinical significance of non-mitotic proliferation in cancer drug resistance and recurrence, and its relationship with cancer stem cells are worthy of further studies.

A Bayesian framework to study tumor subclone-specific expression by combining bulk DNA and single-cell RNA sequencing data

Genetic and gene expression heterogeneity is an essential hallmark of many tumors, allowing the cancer to evolve and to develop resistance to treatment. Currently, the most commonly used data types for studying such heterogeneity are bulk tumor/normal whole-genome or whole-exome sequencing (WGS, WES); and single-cell RNA sequencing (scRNA-seq), respectively. However, tools are currently lacking to link genomic tumor subclonality with transcriptomic heterogeneity by integrating genomic and single-cell transcriptomic data collected from the same tumor. To address this gap, we developed scBayes, a Bayesian probabilistic framework that uses tumor subclonal structure inferred from bulk DNA sequencing data to determine the subclonal identity of cells from single-cell gene expression (scRNA-seq) measurements. Grouping together cells representing the same genetically defined tumor subclones allows comparison of gene expression across different subclones, or investigation of gene expression changes within the same subclone across time (i.e., progression, treatment response, or relapse) or space (i.e., at multiple metastatic sites and organs). We used simulated data sets, in silico synthetic data sets, as well as biological data sets generated from cancer samples to extensively characterize and validate the performance of our method, as well as to show improvements over existing methods. We show the validity and utility of our approach by applying it to published data sets and recapitulating the findings, as well as arriving at novel insights into cancer subclonal expression behavior in our own data sets. We further show that our method is applicable to a wide range of single-cell sequencing technologies including single-cell DNA sequencing as well as Smart-seq and 10x Genomics scRNA-seq protocols.

Multidimensional progressive single-cell sequencing reveals cell microenvironment composition and cancer heterogeneity in lung cancer

Despite substantial advances in cancer biology and treatment, the clinical outcomes of patients with lung cancer remain unsatisfactory. The tumor microenvironment (TME) is a potential target. Using single-cell RNA sequencing, we could distinguish eight distinct cell types in the lung cancer microenvironment, demonstrating substantial intratumoral heterogeneity in 19 different lung cancer tumor samples. Through the re-dimensional grouping of cancer-associated fibroblasts (CAFs), myeloid cells, epithelial cells, natural killer (NK) cells, and T cells, the difference in the TME of lung cancer was revealed. We discovered SFTPB, SFN, and KRT8 as possible predictive biomarkers for lung cancer by assessing the gene expression patterns in epithelial cells. Examining cell-to-cell communications showed a robust association between the quantity of matrix CAFs, epithelial cells, and macrophages in the thrombospondin signaling pathway. Additionally, we found that the amyloid precursor protein signaling pathway primarily originated from the matrix, and inflammatory cancer-associated endothelial and fibroblast cells showed a co-expression relationship with myeloid cells and B cells. Through cell-to-cell correlation analysis, we found positive regulation between NK cells, regulatory T cells, GZMB-CD8 T cells, and GZMK-CD8 T cells, which could play a role in developing immune TMEs. These findings support studies on cancer heterogeneity and add to our understanding of lung cancer's cellular microenvironment.

Bioinformatics and Experimental Validation for Identifying Biomarkers Associated with AMG510 (Sotorasib) Resistance in KRASG12C-Mutated Lung Adenocarcinoma

The Kirsten rat sarcoma viral oncogene homolog (KRAS)G12C mutation is prevalent in lung adenocarcinoma (LUAD), driving tumor progression and indicating a poor prognosis. While the FDA-approved AMG510 (Sotorasib) initially demonstrated efficacy in treating KRASG12C-mutated LUAD, resistance emerged within months. Data from AMG510 treatment-resistant LUAD (GSE204753) and single-cell datasets (GSE149655) were analyzed. Gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) were used to explore enriched signaling pathways, nomogram models were constructed, and transcription factors predicting resistance biomarkers were predicted. CIBERSORT identified immune cell subpopulations, and their association with resistance biomarkers was assessed through single-cell analysis. AMG510-resistant LUAD cells (H358-AR) were constructed, and proliferative changes were evaluated using a CCK-8 assay. Key molecules for AMG510 resistance, including SLC2A1, TLE1, FAM83A, HMGA2, FBXO44, and MTRNR2L12, were recognized. These molecules impacted multiple signaling pathways and the tumor microenvironment and were co-regulated by various transcription factors. Single-cell analysis revealed a dampening effect on immune cell function, with associations with programmed cell death ligand 1 (PDL1) expression, cytokine factors, and failure factors. The findings indicate that these newly identified biomarkers are linked to the abnormal expression of PDL1 and have the potential to induce resistance through immunosuppression. These results highlight the need for further research and therapeutic intervention to address this issue effectively.

Key processes in tumor metastasis and therapeutic strategies with nanocarriers: a review

Cancer metastasis is the leading cause of cancer-related death. Metastasis occurs at all stages of tumor development, with unexplored changes occurring at the primary site and distant colonization sites. The growing understanding of the metastatic process of tumor cells has contributed to the emergence of better treatment options and strategies. This review summarizes a range of features related to tumor cell metastasis and nanobased drug delivery systems for inhibiting tumor metastasis. The mechanisms of tumor metastasis in the ideal order of metastatic progression were summarized. We focus on the prominent role of nanocarriers in the treatment of tumor metastasis, summarizing the latest applications of nanocarriers in combination with drugs to target important components and processes of tumor metastasis and providing ideas for more effective nanodrug delivery systems.

Proteomic, Metabolomic, and Fatty Acid Profiling of Small Extracellular Vesicles from Glioblastoma Stem-Like Cells and Their Role in Tumor Heterogeneity

Glioblastoma is a deadly brain tumor for which there is no cure. The presence of glioblastoma stem-like cells (GSCs) contributes to the heterogeneous nature of the disease and makes developing effective therapies challenging. Glioblastoma cells have been shown to influence their environment by releasing biological nanostructures known as extracellular vesicles (EVs). Here, we investigated the role of GSC-derived nanosized EVs (<200 nm) in glioblastoma heterogeneity, plasticity, and aggressiveness, with a particular focus on their protein, metabolite, and fatty acid content. We showed that conditioned medium and small extracellular vesicles (sEVs) derived from cells of one glioblastoma subtype induced transcriptomic and proteomic changes in cells of another subtype. We found that GSC-derived sEVs are enriched in proteins playing a role in the transmembrane transport of amino acids, carboxylic acids, and organic acids, growth factor binding, and metabolites associated with amino acid, carboxylic acid, and sugar metabolism. This suggests a dual role of GSC-derived sEVs in supplying neighboring GSCs with valuable metabolites and proteins responsible for their transport. Moreover, GSC-derived sEVs were enriched in saturated fatty acids, while their respective cells were high in unsaturated fatty acids, supporting that the loading of biological cargos into sEVs is a highly regulated process and that GSC-derived sEVs could be sources of saturated fatty acids for the maintenance of glioblastoma cell metabolism. Interestingly, sEVs isolated from GSCs of the proneural and mesenchymal subtypes are enriched in specific sets of proteins, metabolites, and fatty acids, suggesting a molecular collaboration between transcriptionally different glioblastoma cells. In summary, this study revealed the complexity of GSC-derived sEVs and unveiled their potential contribution to tumor heterogeneity and critical cellular processes commonly deregulated in glioblastoma.

Dynamic IL-6R/STAT3 signaling leads to heterogeneity of metabolic phenotype in pancreatic ductal adenocarcinoma cells

Malignancy is enabled by pro-growth mutations and adequate energy provision. However, global metabolic activation would be self-terminating if it depleted tumor resources. Cancer cells could avoid this by rationing resources, e.g., dynamically switching between "baseline" and "activated" metabolic states. Using single-cell metabolic phenotyping of pancreatic ductal adenocarcinoma cells, we identify MIA-PaCa-2 as having broad heterogeneity of fermentative metabolism. Sorting by a readout of lactic acid permeability separates cells by fermentative and respiratory rates. Contrasting phenotypes persist for 4 days and are unrelated to cell cycling or glycolytic/respiratory gene expression; however, transcriptomics links metabolically active cells with interleukin-6 receptor (IL-6R)-STAT3 signaling. We verify this by IL-6R/STAT3 knockdowns and sorting by IL-6R status. IL-6R/STAT3 activates fermentation and transcription of its inhibitor, SOCS3, resulting in delayed negative feedback that underpins transitions between metabolic states. Among cells manifesting wide metabolic heterogeneity, dynamic IL-6R/STAT3 signaling may allow cell cohorts to take turns in progressing energy-intense processes without depleting shared resources.