Clonal Heterogeneity and Tumor Evolution: Past, Present, and the Future

Inferring therapeutic vulnerability within tumors through integration of pan-cancer cell line and single-cell transcriptomic profiles

Single-cell RNA sequencing greatly advanced our understanding of intratumoral heterogeneity through identifying tumor subpopulations with distinct biologies. However, translating biological differences into treatment strategies is challenging, as we still lack tools to facilitate efficient drug discovery that tackles heterogeneous tumors. One key component of such approaches tackles accurate prediction of drug response at the single-cell level to offer therapeutic options to specific cell subpopulations. Here, we present a transparent computational framework (nicknamed scIDUC) to predict therapeutic efficacies on an individual-cell basis by integrating single-cell transcriptomic profiles with large, data-rich pan-cancer cell line screening datasets. Our method achieves high accuracy, with predicted sensitivities easily able to separate cells into their true cellular drug resistance status as measured by effect size (Cohen's d > 1.0). More importantly, we examine our method's utility with three distinct prospective tests covering different diseases (rhabdomyosarcoma, pancreatic ductal adenocarcinoma, and castration-resistant prostate cancer), and in each our predicted results are accurate and mirrored biological expectations. In the first two, we identified drugs for cell subpopulations that are resistant to standard-of-care (SOC) therapies due to intrinsic resistance or effects of tumor microenvironments. Our results showed high consistency with experimental findings from the original studies. In the third test, we generated SOC therapy resistant cell lines, used scIDUC to identify efficacious drugs for the resistant line, and validated the predictions with in-vitro experiments. Together, scIDUC quickly translates scRNA-seq data into drug response for individual cells, displaying the potential as a first-line tool for nuanced and heterogeneity-aware drug discovery.

Chromosome instability and aneuploidy in the mammalian brain

This review investigates the role of aneuploidy and chromosome instability (CIN) in the aging brain. Aneuploidy refers to an abnormal chromosomal count, deviating from the normal diploid set. It can manifest as either a deficiency or excess of chromosomes. CIN encompasses a broader range of chromosomal alterations, including aneuploidy as well as structural modifications in DNA. We provide an overview of the state-of-the-art methodologies utilized for studying aneuploidy and CIN in non-tumor somatic tissues devoid of clonally expanded populations of aneuploid cells.CIN and aneuploidy, well-established hallmarks of cancer cells, are also associated with the aging process. In non-transformed cells, aneuploidy can contribute to functional impairment and developmental disorders. Despite the importance of understanding the prevalence and specific consequences of aneuploidy and CIN in the aging brain, these aspects remain incompletely understood, emphasizing the need for further scientific investigations.This comprehensive review consolidates the present understanding, addresses discrepancies in the literature, and provides valuable insights for future research efforts.

Neo-Antigen-Reactive T Cells Immunotherapy for Colorectal Cancer: A More Personalized Cancer Therapy Approach

Colorectal cancer (CRC) is the second most common malignancy in women and the third most frequent cancer in men. Evidence has revealed that the survival of patients with metastatic CRC is very low, between one and three years. Neoantigens are known proteins encoded by mutations in tumor cells. It is theorized that recognizing neoantigens by T cells leads to T cell activation and further antitumor responses. Neoantigen-reactive T cells (NRTs) are designed against the mentioned neoantigens expressed by tumor cells. NRTs selectively kill tumor cells without damage to non-cancerous cells. Identifying patient-specific and high immunogen neoantigens is important in NRT immunotherapy of patients with CRC. However, the main challenges are the side effects and preparation of NRTs, as well as the effectiveness of these cells in vivo. This review summarized the properties of neoantigens as well as the preparation and therapeutic outcomes of NRTs for the treatment of CRC.

Vitamin B5 supports MYC oncogenic metabolism and tumor progression in breast cancer

Tumors are intrinsically heterogeneous and it is well established that this directs their evolution, hinders their classification and frustrates therapy1-3. Consequently, spatially resolved omics-level analyses are gaining traction4-9. Despite considerable therapeutic interest, tumor metabolism has been lagging behind this development and there is a paucity of data regarding its spatial organization. To address this shortcoming, we set out to study the local metabolic effects of the oncogene c-MYC, a pleiotropic transcription factor that accumulates with tumor progression and influences metabolism10,11. Through correlative mass spectrometry imaging, we show that pantothenic acid (vitamin B5) associates with MYC-high areas within both human and murine mammary tumors, where its conversion to coenzyme A fuels Krebs cycle activity. Mechanistically, we show that this is accomplished by MYC-mediated upregulation of its multivitamin transporter SLC5A6. Notably, we show that SLC5A6 over-expression alone can induce increased cell growth and a shift toward biosynthesis, whereas conversely, dietary restriction of pantothenic acid leads to a reversal of many MYC-mediated metabolic changes and results in hampered tumor growth. Our work thus establishes the availability of vitamins and cofactors as a potential bottleneck in tumor progression, which can be exploited therapeutically. Overall, we show that a spatial understanding of local metabolism facilitates the identification of clinically relevant, tractable metabolic targets.

A Bayesian method to infer copy number clones from single-cell RNA and ATAC sequencing

Single-cell RNA and ATAC sequencing technologies enable the examination of gene expression and chromatin accessibility in individual cells, providing insights into cellular phenotypes. In cancer research, it is important to consistently analyze these states within an evolutionary context on genetic clones. Here we present CONGAS+, a Bayesian model to map single-cell RNA and ATAC profiles onto the latent space of copy number clones. CONGAS+ clusters cells into tumour subclones with similar ploidy, rendering straightforward to compare their expression and chromatin profiles. The framework, implemented on GPU and tested on real and simulated data, scales to analyse seamlessly thousands of cells, demonstrating better performance than single-molecule models, and supporting new multi-omics assays. In prostate cancer, lymphoma and basal cell carcinoma, CONGAS+ successfully identifies complex subclonal architectures while providing a coherent mapping between ATAC and RNA, facilitating the study of genotype-phenotype maps and their connection to genomic instability.

The updates on metastatic mechanism and treatment of colorectal cancer

Colorectal cancer (CRC) is a main cause of cancer death worldwide. Metastasis is a major cause of cancer-related death in CRC. The treatment of metastatic CRC has progressed minimally. However, the potential molecular mechanisms involved in CRC metastasis have remained to be comprehensively clarified. An improved understanding of the CRC mechanistic determinants is needed to better prevent and treat metastatic cancer. In this review, based on evidence from a growing body of research in metastatic cancers, we discuss the cellular and molecular mechanisms involved in CRC metastasis. This review reveals both the molecular mechanisms of metastases and identifies new opportunities for developing more effective strategies to target metastatic relapse and improve CRC patient outcomes.

Robust deep learning-based PET prognostic imaging biomarker for DLBCL patients: a multicenter study

OBJECTIVE

To develop and independently externally validate robust prognostic imaging biomarkers distilled from PET images using deep learning techniques for precise survival prediction in patients with diffuse large B cell lymphoma (DLBCL).

METHODS

A total of 684 DLBCL patients from three independent medical centers were included in this retrospective study. Deep learning scores (DLS) were generated from PET images using deep convolutional neural network architecture known as VGG19 and DenseNet121. These DLSs were utilized to predict progression-free survival (PFS) and overall survival (OS). Furthermore, multiparametric models were designed based on results from the Cox proportional hazards model and assessed through calibration curves, concordance index (C-index), and decision curve analysis (DCA) in the training and validation cohorts.

RESULTS

The DLSPFS and DLSOS exhibited significant associations with PFS and OS, respectively (P<0.05) in the training and validation cohorts. The multiparametric models that incorporated DLSs demonstrated superior efficacy in predicting PFS (C-index: 0.866) and OS (C-index: 0.835) compared to competing models in training cohorts. In external validation cohorts, the C-indices for PFS and OS were 0.760 and. 0.770 and 0.748 and 0.766, respectively, indicating the reliable validity of the multiparametric models. The calibration curves displayed good consistency, and the decision curve analysis (DCA) confirmed that the multiparametric models offered more net clinical benefits.

CONCLUSIONS

The DLSs were identified as robust prognostic imaging biomarkers for survival in DLBCL patients. Moreover, the multiparametric models developed in this study exhibited promising potential in accurately stratifying patients based on their survival risk.

Cancer vaccine strategies for the treatment of diffusely infiltrating gliomas

Diffusely infiltrating gliomas - including glioblastoma (GBM), isocitrate dehydrogenase (IDH) mutant gliomas, and histone 3 (H3) altered gliomas - are primary brain tumors with an invariably fatal outcome. Despite advances in the understanding of their biology, standard, targeted and immune checkpoint inhibitor immunotherapies have proven ineffective in arresting their inexorable progression and associated morbidity and mortality. Recognizing the unique aspects of the immunogenicity of cancer cells, the last decade has seen the development and evaluation of vaccine-based therapies for the treatment of solid tumors, including gliomas. Here we review the current vaccine strategies for the treatment of GBM, IDH-mutant gliomas and diffuse midline glioma H3 K27M-altered. We discuss potential benefits and challenges of vaccine therapies in these specific patient populations.

It's high-time to re-evaluate the value of induced-chemotherapy for reinforcing immunotherapy in colorectal cancer

Immunotherapy has made significant advances in the treatment of colorectal cancer (CRC), revolutionizing the therapeutic landscape and highlighting the indispensable role of the tumor immune microenvironment. However, some CRCs have shown poor response to immunotherapy, prompting investigation into the underlying reasons. It has been discovered that certain chemotherapeutic agents possess immune-stimulatory properties, including the induction of immunogenic cell death (ICD), the generation and processing of non-mutated neoantigens (NM-neoAgs), and the B cell follicle-driven T cell response. Based on these findings, the concept of inducing chemotherapy has been introduced, and the combination of inducing chemotherapy and immunotherapy has become a standard treatment option for certain cancers. Clinical trials have confirmed the feasibility and safety of this approach in CRC, offering a promising method for improving the efficacy of immunotherapy. Nevertheless, there are still many challenges and difficulties ahead, and further research is required to optimize its use.

Mitochondria in oral cancer stem cells: Unraveling the potential drug targets for new and old drugs

Head and neck cancer is a major health problem worldwide, with most cases arising in the oral cavity. Oral squamous cell carcinoma (OSCC) is the most common type of oral cancer, accounting for over 90% of all cases. Compared to other types of cancer, OSCC, has the worse prognosis, with a 5-year survival rate of 50%. Additionally, OSCC is characterized by a high rate of resistance to chemotherapy treatment, which may be partly explained by the presence of cancer stem cells (CSC) subpopulation. CSC can adapt to harmful environmental condition and are highly resistant to both chemotherapy and radiotherapy treatments, thus contributing to tumor relapse. The aim of this review is to highlight the role of mitochondria in oral CSC as a potential target for oral cancer treatment. For this purpose, we reviewed some fundamental aspects of the most validated protein markers of stemness, autophagy, the mitochondrial function and energy metabolism in oral CSC. Moreover, a discussion will be made on why energy metabolism, especially oxidative phosphorylation in CSC, may offer such a diverse source of original pharmacological target for new drugs. Finally, we will describe some drugs able to disturb mitochondrial function, with emphasis on those aimed to interrupt the electron transport chain function, as novel therapeutic strategies in multidrug-resistant oral CSC. The reutilization of old drugs approved for clinical use as new antineoplastics, in cancer treatment, is also matter of revision.

A live-cell platform to isolate phenotypically defined subpopulations for spatial multi-omic profiling

Numerous techniques have been employed to deconstruct the heterogeneity observed in normal and diseased cellular populations, including single cell RNA sequencing, in situ hybridization, and flow cytometry. While these approaches have revolutionized our understanding of heterogeneity, in isolation they cannot correlate phenotypic information within a physiologically relevant live-cell state with molecular profiles. This inability to integrate a live-cell phenotype-such as invasiveness, cell:cell interactions, and changes in spatial positioning-with multi-omic data creates a gap in understanding cellular heterogeneity. We sought to address this gap by employing lab technologies to design a detailed protocol, termed Spatiotemporal Genomic and Cellular Analysis (SaGA), for the precise imaging-based selection, isolation, and expansion of phenotypically distinct live cells. This protocol requires cells expressing a photoconvertible fluorescent protein and employs live cell confocal microscopy to photoconvert a user-defined single cell or set of cells displaying a phenotype of interest. The total population is then extracted from its microenvironment, and the optically highlighted cells are isolated using fluorescence activated cell sorting. SaGA-isolated cells can then be subjected to multi-omics analysis or cellular propagation for in vitro or in vivo studies. This protocol can be applied to a variety of conditions, creating protocol flexibility for user-specific research interests. The SaGA technique can be accomplished in one workday by non-specialists and results in a phenotypically defined cellular subpopulations for integration with multi-omics techniques. We envision this approach providing multi-dimensional datasets exploring the relationship between live cell phenotypes and multi-omic heterogeneity within normal and diseased cellular populations.

Single-cell sequencing technology applied to epigenetics for the study of tumor heterogeneity

BACKGROUND

Previous studies have traditionally attributed the initiation of cancer cells to genetic mutations, considering them as the fundamental drivers of carcinogenesis. However, recent research has shed light on the crucial role of epigenomic alterations in various cell types present within the tumor microenvironment, suggesting their potential contribution to tumor formation and progression. Despite these significant findings, the progress in understanding the epigenetic mechanisms regulating tumor heterogeneity has been impeded over the past few years due to the lack of appropriate technical tools and methodologies.

RESULTS

The emergence of single-cell sequencing has enhanced our understanding of the epigenetic mechanisms governing tumor heterogeneity by revealing the distinct epigenetic layers of individual cells (chromatin accessibility, DNA/RNA methylation, histone modifications, nucleosome localization) and the diverse omics (transcriptomics, genomics, multi-omics) at the single-cell level. These technologies provide us with new insights into the molecular basis of intratumoral heterogeneity and help uncover key molecular events and driving mechanisms in tumor development.

CONCLUSION

This paper provides a comprehensive review of the emerging analytical and experimental approaches of single-cell sequencing in various omics, focusing specifically on epigenomics. These approaches have the potential to capture and integrate multiple dimensions of individual cancer cells, thereby revealing tumor heterogeneity and epigenetic features. Additionally, this paper outlines the future trends of these technologies and their current technical limitations.

Single-Cell Diagnosis of Cancer Drug Resistance through the Differential Endocytosis of Nanoparticles between Drug-Resistant and Drug-Sensitive Cancer Cells

Single-cell diagnosis of cancer drug resistance is highly relevant for cancer treatment, as it can be used to identify the subpopulations of drug-resistant cancer cells, reveal the sensitivity of cancer cells to treatment, and monitor the progress of cancer drug resistance. However, simple and effective methods for cancer drug resistance detection at the single-cell level are still lacking in laboratory and clinical studies. Inspired by the fact that nanoparticles with diverse physicochemical properties would generate distinct and specific interactions with drug-resistant and drug-sensitive cancer cells, which have distinctive molecular signatures, here, we have synthesized a library of fluorescent nanoparticles with various sizes, surface charges, and compositions (SiO2 nanoparticles (SNPs), organic PS-co-PAA nanoparticles (ONPs), and ZIF-8 nanoparticles (ZNPs)), thus demonstrating that the composition has a critical influence on the interaction of nanoparticles with drug-resistant cancer cells. Furthermore, the clathrin/caveolae-independent endocytosis of ZNPs together with the P-glycoprotein-related decreased cell membrane fluidity resulted in a lower cellular accumulation of ZNPs in drug-resistant cancer cells, consequently causing the distinct cellular accumulation of ZNPs between the drug-resistant and drug-sensitive cancer cells. This difference was further quantified by detecting the fluorescence signals generated by the accumulation of nanoparticles at the single-cell level via flow cytometry. Our findings provide another insight into the nanoparticle-cell interactions and offer a promising platform for the diagnosis of cancer drug resistance of various cancer cells and clinical cancer samples at the single-cell level.

Cancer cell-intrinsic mechanisms driving acquired immune tolerance

Immune evasion is a hallmark of cancer, enabling tumors to survive contact with the host immune system and evade the cycle of immune recognition and destruction. Here, we review the current understanding of the cancer cell-intrinsic factors driving immune evasion. We focus on T cells as key effectors of anti-cancer immunity and argue that cancer cells evade immune destruction by gaining control over pathways that usually serve to maintain physiological tolerance to self. Using this framework, we place recent mechanistic advances in the understanding of cancer immune evasion into broad categories of control over T cell localization, antigen recognition, and acquisition of optimal effector function. We discuss the redundancy in the pathways involved and identify knowledge gaps that must be overcome to better target immune evasion, including the need for better, routinely available tools that incorporate the growing understanding of evasion mechanisms to stratify patients for therapy and trials.

Radiogenomic-based multiomic analysis reveals imaging intratumor heterogeneity phenotypes and therapeutic targets

Intratumor heterogeneity (ITH) profoundly affects therapeutic responses and clinical outcomes. However, the widespread methods for assessing ITH based on genomic sequencing or pathological slides, which rely on limited tissue samples, may lead to inaccuracies due to potential sampling biases. Using a newly established multicenter breast cancer radio-multiomic dataset (n = 1474) encompassing radiomic features extracted from dynamic contrast-enhanced magnetic resonance images, we formulated a noninvasive radiomics methodology to effectively investigate ITH. Imaging ITH (IITH) was associated with genomic and pathological ITH, predicting poor prognosis independently in breast cancer. Through multiomic analysis, we identified activated oncogenic pathways and metabolic dysregulation in high-IITH tumors. Integrated metabolomic and transcriptomic analyses highlighted ferroptosis as a vulnerability and potential therapeutic target of high-IITH tumors. Collectively, this work emphasizes the superiority of radiomics in capturing ITH. Furthermore, we provide insights into the biological basis of IITH and propose therapeutic targets for breast cancers with elevated IITH.

Epithelial ovarian cancer is infiltrated by activated effector T cells co-expressing CD39, PD-1, TIM-3, CD137 and interacting with cancer cells and myeloid cells

Introduction

Despite predicted efficacy, immunotherapy in epithelial ovarian cancer (EOC) has limited clinical benefit and the prognosis of patients remains poor. There is thus a strong need for better identifying local immune dynamics and immune-suppressive pathways limiting T-cell mediated anti-tumor immunity.

Methods

In this observational study we analyzed by immunohistochemistry, gene expression profiling and flow cytometry the antigenic landscape and immune composition of 48 EOC specimens, with a focus on tumor-infiltrating lymphocytes (TILs).

Results

Activated T cells showing features of partial exhaustion with a CD137+CD39+PD-1+TIM-3+CD45RA-CD62L-CD95+ surface profile were exclusively present in EOC specimens but not in corresponding peripheral blood or ascitic fluid, indicating that the tumor microenvironment might sustain this peculiar phenotype. Interestingly, while neoplastic cells expressed several tumor-associated antigens possibly able to stimulate tumor-specific TILs, macrophages provided both co-stimulatory and inhibitory signals and were more abundant in TILs-enriched specimens harboring the CD137+CD39+PD-1+TIM-3+CD45RA-CD62L-CD95+ signature.

Conclusion

These data demonstrate that EOC is enriched in CD137+CD39+PD-1+TIM-3+CD45RA-CD62L-CD95+ T lymphocytes, a phenotype possibly modulated by antigen recognition on neoplastic cells and by a combination of inhibitory and co-stimulatory signals largely provided by infiltrating myeloid cells. Furthermore, we have identified immunosuppressive pathways potentially hampering local immunity which might be targeted by immunotherapeutic approaches.

Polyglycerol-Based Biomedical Matrix for Immunomagnetic Circulating Tumor Cell Isolation and Their Expansion into Tumor Spheroids for Drug Screening

Circulating tumor cells (CTCs) are established as distinct cancer biomarkers for diagnosis, as preclinical models, and therapeutic targets. Their use as preclinical models is limited owing to low purity after isolation and the lack of effective techniques to create 3D cultures that accurately mimic in vivo conditions. Herein, a two-component system for detecting, isolating, and expanding CTCs to generate multicellular tumor spheroids that mimic the physiology and microenvironment of the diseased organ is proposed. First, an antifouling biointerface on magnetic beads is fabricated by adding a bioinert polymer layer and conjugation of biospecific ligands to isolate cancer cells, dramatically enhancing the selectivity and purity of the isolated cancer cells. Next, the isolated cells are encapsulated into self-degradable hydrogels synthesized using a thiol-click approach. The hydrogels are mechanochemically tuned to enable tumor spheroid growth to a size greater than 300 µm and to further release the grown spheroids while retaining their tumor-like characteristics. In addition, drug treatment highlights the need for 3D culture environments rather than conventional 2D culture. The designed biomedical matrix shows potential as a universal method to ensure mimicry of in vivo tumor characteristics in individual patients and to improve the predictability of preclinical screening of personalized therapeutics.

Mismatch repair deficiency is not sufficient to elicit tumor immunogenicity

DNA mismatch repair deficiency (MMRd) is associated with a high tumor mutational burden (TMB) and sensitivity to immune checkpoint blockade (ICB) therapy. Nevertheless, most MMRd tumors do not durably respond to ICB and critical questions remain about immunosurveillance and TMB in these tumors. In the present study, we developed autochthonous mouse models of MMRd lung and colon cancer. Surprisingly, these models did not display increased T cell infiltration or ICB response, which we showed to be the result of substantial intratumor heterogeneity of mutations. Furthermore, we found that immunosurveillance shapes the clonal architecture but not the overall burden of neoantigens, and T cell responses against subclonal neoantigens are blunted. Finally, we showed that clonal, but not subclonal, neoantigen burden predicts ICB response in clinical trials of MMRd gastric and colorectal cancer. These results provide important context for understanding immune evasion in cancers with a high TMB and have major implications for therapies aimed at increasing TMB.

Optimal timing for local ablative treatment of bone oligometastases in non-small cell lung cancer

Oligometastases is a term commonly used to describe a disease state characterized by a limited number of distant metastases, and represents a transient phase between localized and widespread systemic diseases. This subgroup of stage IV cancer has increased in clinical importance due to the possibility of curative rather than palliative treatment. Among advanced lung cancer patients, 30-40% show bone metastases, and can show complications such as pathological fractures. Many prospective studies have shown efficacy of localized treatment in oligometastatic non-small cell lung cancer (NSCLC) in improving progression-free survival and overall survival. Compared to metastases in other organs, bone metastases are unique in terms of tumor microenvironment and clinical outcomes. Radiotherapy is the most frequently used treatment modality for local ablative treatment for both primary and metastatic lesions. Stereotactic body radiation therapy demonstrated more rapid and effective pain control compared to conventional 3D conformal radiotherapy. Radiotherapy improved outcomes in terms of time-to-skeletal related events skeletal-related events (SRE), hospitalization for SRE, pain relief, and overall survival in patients with bone metastases. Decision on timing of local ablative treatment depends on patient's overall clinical status, treatment goals, potential side effects of each approach, and expected initial responses to systemic anti-cancer treatment.

The crosstalk between ferroptosis and anti-tumor immunity in the tumor microenvironment: molecular mechanisms and therapeutic controversy

The advent of immunotherapy has significantly reshaped the landscape of cancer treatment, greatly enhancing therapeutic outcomes for multiple types of cancer. However, only a small subset of individuals respond to it, underscoring the urgent need for new methods to improve its response rate. Ferroptosis, a recently discovered form of programmed cell death, has emerged as a promising approach for anti-tumor therapy, with targeting ferroptosis to kill tumors seen as a potentially effective strategy. Numerous studies suggest that inducing ferroptosis can synergistically enhance the effects of immunotherapy, paving the way for a promising combined treatment method in the future. Nevertheless, recent research has raised concerns about the potential negative impacts on anti-tumor immunity as a consequence of inducing ferroptosis, leading to conflicting views within the scientific community about the interplay between ferroptosis and anti-tumor immunity, thereby underscoring the necessity of a comprehensive review of the existing literature on this relationship. Previous reviews on ferroptosis have touched on related content, many focusing primarily on the promoting role of ferroptosis on anti-tumor immunity while overlooking recent evidence on the inhibitory effects of ferroptosis on immunity. Others have concentrated solely on discussing related content either from the perspective of cancer cells and ferroptosis or from immune cells and ferroptosis. Given that both cancer cells and immune cells exist in the tumor microenvironment, a one-sided discussion cannot comprehensively summarize this topic. Therefore, from the perspectives of both tumor cells and tumor-infiltrating immune cells, we systematically summarize the current conflicting views on the interplay between ferroptosis and anti-tumor immunity, intending to provide potential explanations and identify the work needed to establish a translational basis for combined ferroptosis-targeted therapy and immunotherapy in treating tumors.

Refphase: Multi-sample phasing reveals haplotype-specific copy number heterogeneity

Most computational methods that infer somatic copy number alterations (SCNAs) from bulk sequencing of DNA analyse tumour samples individually. However, the sequencing of multiple tumour samples from a patient's disease is an increasingly common practice. We introduce Refphase, an algorithm that leverages this multi-sampling approach to infer haplotype-specific copy numbers through multi-sample phasing. We demonstrate Refphase's ability to infer haplotype-specific SCNAs and characterise their intra-tumour heterogeneity, to uncover previously undetected allelic imbalance in low purity samples, and to identify parallel evolution in the context of whole genome doubling in a pan-cancer cohort of 336 samples from 99 tumours.

Assessing the performance of methods for cell clustering from single-cell DNA sequencing data

BACKGROUND

Many cancer genomes have been known to contain more than one subclone inside one tumor, the phenomenon of which is called intra-tumor heterogeneity (ITH). Characterizing ITH is essential in designing treatment plans, prognosis as well as the study of cancer progression. Single-cell DNA sequencing (scDNAseq) has been proven effective in deciphering ITH. Cells corresponding to each subclone are supposed to carry a unique set of mutations such as single nucleotide variations (SNV). While there have been many studies on the cancer evolutionary tree reconstruction, not many have been proposed that simply characterize the subclonality without tree reconstruction. While tree reconstruction is important in the study of cancer evolutionary history, typically they are computationally expensive in terms of running time and memory consumption due to the huge search space of the tree structure. On the other hand, subclonality characterization of single cells can be converted into a cell clustering problem, the dimension of which is much smaller, and the turnaround time is much shorter. Despite the existence of a few state-of-the-art cell clustering computational tools for scDNAseq, there lacks a comprehensive and objective comparison under different settings.

RESULTS

In this paper, we evaluated six state-of-the-art cell clustering tools-SCG, BnpC, SCClone, RobustClone, SCITE and SBMClone-on simulated data sets given a variety of parameter settings and a real data set. We designed a simulator specifically for cell clustering, and compared these methods' performances in terms of their clustering accuracy, specificity and sensitivity and running time. For SBMClone, we specifically designed an ultra-low coverage large data set to evaluate its performance in the face of an extremely high missing rate.

CONCLUSION

From the benchmark study, we conclude that BnpC and SCG's clustering accuracy are the highest and comparable to each other. However, BnpC is more advantageous in terms of running time when cell number is high (> 1500). It also has a higher clustering accuracy than SCG when cluster number is high (> 16). SCClone's accuracy in estimating the number of clusters is the highest. RobustClone and SCITE's clustering accuracy are the lowest for all experiments. SCITE tends to over-estimate the cluster number and has a low specificity, whereas RobustClone tends to under-estimate the cluster number and has a much lower sensitivity than other methods. SBMClone produced reasonably good clustering (V-measure > 0.9) when coverage is > = 0.03 and thus is highly recommended for ultra-low coverage large scDNAseq data sets.

Tumor-specific cholinergic CD4+ T lymphocytes guide immunosurveillance of hepatocellular carcinoma

Cholinergic nerves are involved in tumor progression and dissemination. In contrast to other visceral tissues, cholinergic innervation in the hepatic parenchyma is poorly detected. It remains unclear whether there is any form of cholinergic regulation of liver cancer. Here, we show that cholinergic T cells curtail the development of liver cancer by supporting antitumor immune responses. In a mouse multihit model of hepatocellular carcinoma (HCC), we observed activation of the adaptive immune response and induction of two populations of CD4+ T cells expressing choline acetyltransferase (ChAT), including regulatory T cells and dysfunctional PD-1+ T cells. Tumor antigens drove the clonal expansion of these cholinergic T cells in HCC. Genetic ablation of Chat in T cells led to an increased prevalence of preneoplastic cells and exacerbated liver cancer due to compromised antitumor immunity. Mechanistically, the cholinergic activity intrinsic in T cells constrained Ca2+-NFAT signaling induced by T cell antigen receptor engagement. Without this cholinergic modulation, hyperactivated CD25+ T regulatory cells and dysregulated PD-1+ T cells impaired HCC immunosurveillance. Our results unveil a previously unappreciated role for cholinergic T cells in liver cancer immunobiology.

Sepsis heterogeneity

BACKGROUND

Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection, with extremely high mortality. Notably, sepsis is a heterogeneous syndrome characterized by a vast, multidimensional array of clinical and biologic features, which has hindered advances in the therapeutic field beyond the current standards.

DATA SOURCES

We used PubMed to search the subject-related medical literature by searching for the following single and/or combination keywords: sepsis, heterogeneity, personalized treatment, host response, infection, epidemiology, mortality, incidence, age, children, sex, comorbidities, gene susceptibility, infection sites, bacteria, fungi, virus, host response, organ dysfunction and management.

RESULTS

We found that host factors (age, biological sex, comorbidities, and genetics), infection etiology, host response dysregulation and multiple organ dysfunctions can all result in different disease manifestations, progression, and response to treatment, which make it difficult to effectively treat and manage sepsis patients.

CONCLUSIONS

Herein, we have summarized contributing factors to sepsis heterogeneity, including host factors, infection etiology, host response dysregulation, and multiple organ dysfunctions, from the key elements of pathogenesis of sepsis. An in-depth understanding of the factors that contribute to the heterogeneity of sepsis will help clinicians understand the complexity of sepsis and enable researchers to conduct more personalized clinical studies for homogenous patients.

Tumor Vaccines: Unleashing the Power of the Immune System to Fight Cancer

This comprehensive review delves into the rapidly evolving arena of cancer vaccines. Initially, we examine the intricate constitution of the tumor microenvironment (TME), a dynamic factor that significantly influences tumor heterogeneity. Current research trends focusing on harnessing the TME for effective tumor vaccine treatments are also discussed. We then provide a detailed overview of the current state of research concerning tumor immunity and the mechanisms of tumor vaccines, describing the complex immunological processes involved. Furthermore, we conduct an exhaustive analysis of the contemporary research landscape of tumor vaccines, with a particular focus on peptide vaccines, DNA/RNA-based vaccines, viral-vector-based vaccines, dendritic-cell-based vaccines, and whole-cell-based vaccines. We analyze and summarize these categories of tumor vaccines, highlighting their individual advantages, limitations, and the factors influencing their effectiveness. In our survey of each category, we summarize commonly used tumor vaccines, aiming to provide readers with a more comprehensive understanding of the current state of tumor vaccine research. We then delve into an innovative strategy combining cancer vaccines with other therapies. By studying the effects of combining tumor vaccines with immune checkpoint inhibitors, radiotherapy, chemotherapy, targeted therapy, and oncolytic virotherapy, we establish that this approach can enhance overall treatment efficacy and offset the limitations of single-treatment approaches, offering patients more effective treatment options. Following this, we undertake a meticulous analysis of the entire process of personalized cancer vaccines, elucidating the intricate process from design, through research and production, to clinical application, thus helping readers gain a thorough understanding of its complexities. In conclusion, our exploration of tumor vaccines in this review aims to highlight their promising potential in cancer treatment. As research in this field continues to evolve, it undeniably holds immense promise for improving cancer patient outcomes.

Recent Advances and Applications of Ambient Mass Spectrometry Imaging in Cancer Research: An Overview

Cancer metabolic variability has a significant impact on both diagnosis and treatment outcomes. The discovery of novel biological indicators and metabolic dysregulation, can significantly rely on comprehension of the modified metabolism in cancer, is a research focus. Tissue histology is a critical feature in the diagnostic testing of many ailments, such as cancer. To assess the surgical margin of the tumour on patients, frozen section histology is a tedious, laborious, and typically arbitrary method. Concurrent monitoring of ion images in tissues facilitated by the latest advancements in mass spectrometry imaging (MSI) is far more efficient than optical tissue image analysis utilized in conventional histopathology examination. This article focuses on the "desorption electrospray ionization (DESI)-MSI" technique's most recent advancements and uses in cancer research. DESI-MSI can provide wealthy information based on the variances in metabolites and lipids in normal and cancerous tissues by acquiring ion images of the lipid and metabolite variances on biopsy samples. As opposed to a systematic review, this article offers a synopsis of the most widely employed cutting-edge DESI-MSI techniques in cancer research.

Integrative bioinformatics analysis of WDHD1: a potential biomarker for pan-cancer prognosis, diagnosis, and immunotherapy

BACKGROUND

Although WD repeat and high-mobility group box DNA binding protein 1 (WDHD1) played an essential role in DNA replication, chromosome stability, and DNA damage repair, the panoramic picture of WDHD1 in human tumors remains unclear. Hence, this study aims to comprehensively characterize WDHD1 across 33 human cancers.

METHODS

Based on publicly available databases such as TCGA, GTEx, and HPA, we used a bioinformatics approach to systematically explore the genomic features and biological functions of WDHD1 in pan-cancer.

RESULTS

WDHD1 mRNA levels were significantly increased in more than 20 types of tumor tissues. Elevated WDHD1 expression was associated with significantly shorter overall survival (OS) in 10 tumors. Furthermore, in uterine corpus endometrial carcinoma (UCEC) and liver hepatocellular carcinoma (LIHC), WDHD1 expression was significantly associated with higher histological grades and pathological stages. In addition, WDHD1 had a high diagnostic value among 16 tumors (area under the ROC curve [AUC] > 0.9). Functional enrichment analyses suggested that WDHD1 probably participated in many oncogenic pathways such as E2F and MYC targets (false discovery rate [FDR] < 0.05), and it was involved in the processes of DNA replication and DNA damage repair (p.adjust < 0.05). WDHD1 expression also correlated with the half-maximal inhibitory concentrations (IC50) of rapamycin (4 out of 10 cancers) and paclitaxel (10 out of 10 cancers). Overall, WDHD1 was negatively associated with immune cell infiltration and might promote tumor immune escape. Our analysis of genomic alterations suggested that WDHD1 was altered in 1.5% of pan-cancer cohorts and the "mutation" was the predominant type of alteration. Finally, through correlation analysis, we found that WDHD1 might be closely associated with tumor heterogeneity, tumor stemness, mismatch repair (MMR), and RNA methylation modification, which were all processes associated with the tumor progression.

CONCLUSIONS

Our pan-cancer analysis of WDHD1 provides valuable insights into the genomic characterization and biological functions of WDHD1 in human cancers and offers some theoretical support for the future use of WDHD1-targeted therapies, immunotherapies, and chemotherapeutic combinations for the management of tumors.

A hybrid breast cancer/mesenchymal stem cell population enhances chemoresistance and metastasis

Patients with triple-negative breast cancer remain at risk for metastatic disease despite treatment. The acquisition of chemoresistance is a major cause of tumor relapse and death, but the mechanisms are far from understood. We have demonstrated that breast cancer cells (BCCs) can engulf mesenchymal stem/stromal cells (MSCs), leading to enhanced dissemination. Here, we show that clinical samples of primary invasive carcinoma and chemoresistant breast cancer metastasis contain a unique hybrid cancer cell population coexpressing pancytokeratin and the MSC marker fibroblast activation protein-α. We show that hybrid cells form in primary tumors and that they promote breast cancer metastasis and chemoresistance. Using single-cell microfluidics and in vivo models, we found that there are polyploid senescent cells within the hybrid cell population that contribute to metastatic dissemination. Our data reveal that Wnt Family Member 5A (WNT5A) plays a crucial role in supporting the chemoresistance properties of hybrid cells. Furthermore, we identified that WNT5A mediates hybrid cell formation through a phagocytosis-like mechanism that requires BCC-derived IL-6 and MSC-derived C-C Motif Chemokine Ligand 2. These findings reveal hybrid cell formation as a mechanism of chemoresistance and suggest that interrupting this mechanism may be a strategy in overcoming breast cancer drug resistance.

Desmosome mutations impact the tumor microenvironment to promote melanoma proliferation

Desmosomes are transmembrane protein complexes that contribute to cell-cell adhesion in epithelia and other tissues. Here, we report the discovery of frequent genetic alterations in the desmosome in human cancers, with the strongest signal seen in cutaneous melanoma where desmosomes are mutated in over 70% of cases. In primary but not metastatic melanoma biopsies, the burden of coding mutations on desmosome genes associates with a strong reduction in desmosome gene expression. Analysis by spatial transcriptomics suggests that these expression decreases occur in keratinocytes in the microenvironment rather than in primary melanoma tumor cells. In further support of a microenvironmental origin, we find that loss-of-function knockdowns of the desmosome in keratinocytes yield markedly increased proliferation of adjacent melanocytes in keratinocyte/melanocyte co-cultures. Thus, gradual accumulation of desmosome mutations in neighboring cells may prime melanocytes for neoplastic transformation.

Cracking the pattern of tumor evolution based on single-cell copy number alterations

Copy number alterations (CNAs) are a key characteristic of tumor development and progression. The accumulation of various CNAs during tumor development plays a critical role in driving tumor evolution. Heterogeneous clones driven by distinct CNAs have different selective advantages, leading to differential patterns of tumor evolution that are essential for developing effective cancer therapies. Recent advances in single-cell sequencing technology have enabled genome-wide copy number profiling of tumor cell populations at single-cell resolution. This has made it possible to explore the evolutionary patterns of CNAs and accurately discover the mechanisms of intra-tumor heterogeneity. Here, we propose a two-step statistical approach that distinguishes neutral, linear, branching and punctuated evolutionary patterns for a tumor cell population based on single-cell copy number profiles. We assessed our approach using a variety of simulated and real single-cell genomic and transcriptomic datasets, demonstrating its high accuracy and robustness in predicting tumor evolutionary patterns. We applied our approach to single-cell DNA sequencing data from 20 breast cancer patients and observed that punctuated evolution is the dominant evolutionary pattern in breast cancer. Similar conclusions were drawn when applying the approach to single-cell RNA sequencing data obtained from 132 various cancer patients. Moreover, we found that differential immune cell infiltration is associated with specific evolutionary patterns. The source code of our study is available at https://github.com/FangWang-SYSU/PTEM.

Multi-disciplinary management of recurrent gastrointestinal stromal tumor harboring KIT exon 11 mutation with the switch-control kinase inhibitor ripretinib and surgery

Ripretinib is a tyrosine kinase inhibitor that was approved by the United States FDA in 2020 for treatment of advanced gastrointestinal stromal tumor (GIST) in patients who received prior treatment with three or more tyrosine kinase inhibitors. In this case report, we show the durable clinical benefit achieved in a patient with GIST by using ripretinib and repeated timely surgical resection of limited disease progression. The total time on ripretinib was 43 months which is longer than the current reported data from ripretinib clinical trials. Such approach for using multi-disciplinary disease management can improve the durability of response to tyrosine kinase inhibitors, including ripretinib, and associated clinical outcomes.

The heterogeneity and clonal evolution analysis of the advanced prostate cancer with castration resistance

BACKGROUND

Nowadays, the incidence rate of advanced and metastatic prostate cancer at the first time of diagnosis grows higher in China yearly. At present, androgen deprivation therapy (ADT) is the primary treatment of advanced prostate cancer. However, after several years of ADT, most patients will ultimately progress to castration-resistant prostate cancer (CRPC). Previous studies mainly focus on Caucasian and very few on East Asian patients.

METHODS

In this study, the pre- and post-ADT tumor samples were collected from five Chinese patients with advanced prostate cancer. The whole-exome sequencing, tumor heterogeneity, and clonal evolution pattern were analyzed.

RESULTS

The results showed that the gene mutation pattern and heterogeneity changed significantly after androgen deprivation therapy. Tumor Mutational Burden (TMB) and Copy Number Alteration (CNA) were substantially reduced in the post-treatment group, but the Mutant-allele tumor heterogeneity (MATH), Socio-Demographic Index (SDI), Intratumor heterogeneity (ITH), and weighted Genome Instability Index (wGII) had no significant difference. According to the clone types and characteristics, the presence of main clones in five pre-and post-treatment samples, the clonal evolution pattern can be further classified into two sub-groups (the Homogeneous origin clonal model or the Heterogeneous origin clonal model). The Progression-free survival (PFS) of the patients with the "Homogeneous origin clonal model" was shorter than the "Heterogeneous origin clonal model". The longer PFS might relate to MUC7 and MUC5B mutations repaired. ZNF91 mutation might be responsible for resistance to ADT resistance.

CONCLUSION

Our findings revealed potential genetic regulators to predict the castration resistance and provide insights into the castration resistance processes in advanced prostate cancer. The crosstalk between clonal evolution patterns and tumor microenvironment may also play a role in castration resistance. A multicenter-research including larger populations with different background are needed to confirm our conclusion in the future.

Crosstalk between endoplasmic reticulum stress and multidrug-resistant cancers: hope or frustration

Endoplasmic reticulum stress (ERS) is a kind of cell response for coping with hypoxia and other stresses. Pieces of evidence show that continuous stress can promote the occurrence, development, and drug resistance of tumors through the unfolded protein response. Therefore, the abnormal ac-tivation of ERS and its downstream signaling pathways not only can regulate tumor growth and metastasis but also profoundly affect the efficacy of antitumor therapy. Therefore, revealing the molecular mechanism of ERS may be expected to solve the problem of tumor multidrug resistance (MDR) and become a novel strategy for the treatment of refractory and recurrent tumors. This re-view summarized the mechanism of ERS and tumor MDR, reviewed the relationship between ERS and tumor MDR, introduced the research status of tumor tissue and ERS, and previewed the prospect of targeting ERS to improve the therapeutic effect of tumor MDR. This article aims to provide researchers and clinicians with new ideas and inspiration for basic antitumor treatment.

A biobank of pediatric patient-derived-xenograft models in cancer precision medicine trial MAPPYACTS for relapsed and refractory tumors

Pediatric patients with recurrent and refractory cancers are in most need for new treatments. This study developed patient-derived-xenograft (PDX) models within the European MAPPYACTS cancer precision medicine trial (NCT02613962). To date, 131 PDX models were established following heterotopical and/or orthotopical implantation in immunocompromised mice: 76 sarcomas, 25 other solid tumors, 12 central nervous system tumors, 15 acute leukemias, and 3 lymphomas. PDX establishment rate was 43%. Histology, whole exome and RNA sequencing revealed a high concordance with the primary patient's tumor profile, human leukocyte-antigen characteristics and specific metabolic pathway signatures. A detailed patient molecular characterization, including specific mutations prioritized in the clinical molecular tumor boards are provided. Ninety models were shared with the IMI2 ITCC Pediatric Preclinical Proof-of-concept Platform (IMI2 ITCC-P4) for further exploitation. This PDX biobank of unique recurrent childhood cancers provides an essential support for basic and translational research and treatments development in advanced pediatric malignancies.

Polycomb safeguards imaginal disc specification through control of the Vestigial-Scalloped complex

A fundamental goal of developmental biology is to understand how cell and tissue fates are specified. The imaginal discs of Drosophila are excellent model systems for addressing this paradigm as their fate can be redirected when discs regenerate after injury or when key selector genes are misregulated. Here, we show that when Polycomb expression is reduced, the wing selector gene vestigial is ectopically activated. This leads to the inappropriate formation of the Vestigial-Scalloped complex, which forces the eye to transform into a wing. We further demonstrate that disrupting this complex does not simply block wing formation or restore eye development. Instead, immunohistochemistry and high-throughput genomic analysis show that the eye-antennal disc unexpectedly undergoes hyperplastic growth with multiple domains being organized into other imaginal discs and tissues. These findings provide insight into the complex developmental landscape that tissues must navigate before adopting their final fate.

A mathematical investigation of polyaneuploid cancer cell memory and cross-resistance in state-structured cancer populations

The polyaneuploid cancer cell (PACC) state promotes cancer lethality by contributing to survival in extreme conditions and metastasis. Recent experimental evidence suggests that post-therapy PACC-derived recurrent populations display cross-resistance to classes of therapies with independent mechanisms of action. We hypothesize that this can occur through PACC memory, whereby cancer cells that have undergone a polyaneuploid transition (PAT) reenter the PACC state more quickly or have higher levels of innate resistance. In this paper, we build on our prior mathematical models of the eco-evolutionary dynamics of cells in the 2N+ and PACC states to investigate these two hypotheses. We show that although an increase in innate resistance is more effective at promoting cross-resistance, this trend can also be produced via PACC memory. We also find that resensitization of cells that acquire increased innate resistance through the PAT have a considerable impact on eco-evolutionary dynamics and extinction probabilities. This study, though theoretical in nature, can help inspire future experimentation to tease apart hypotheses surrounding how cross-resistance in structured cancer populations arises.

An exploratory study of cell stiffness as a mechanical label-free biomarker across multiple musculoskeletal sarcoma cells

BACKGROUND

Cancer cells are characterized by changes in cell cytoskeletal architecture and stiffness. Despite advances in understanding the molecular mechanisms of musculoskeletal cancers, the corresponding cellular mechanical properties remain largely unexplored. The aim of this study was to investigate the changes in cellular stiffness and the associated cytoskeleton configuration alterations in various musculoskeletal cancer cells.

METHODS

Cell lines from five main sarcoma types of the musculoskeletal system (chondrosarcoma, osteosarcoma, Ewing sarcoma, fibrosarcoma and rhabdomyosarcoma) as well as their healthy cell counterparts (chondrocytes, osteoblasts, mesenchymal stem cells, fibroblasts, skeletal muscle cells) were subjected to cell stiffness measurements via atomic force microscopy (AFM). Biochemical and structural changes of the cytoskeleton (F-actin, β-tubulin and actin-related protein 2/3) were assessed by means of fluorescence labelling, ELISA and qPCR.

RESULTS

While AFM stiffness measurements showed that the majority of cancer cells (osteosarcoma, Ewing sarcoma, fibrosarcoma and rhabdomyosarcoma) were significantly less stiff than their corresponding non-malignant counterparts (p < 0.001), the chondrosarcoma cells were significant stiffer than the chondrocytes (p < 0.001). Microscopically, the distribution of F-actin differed between malignant entities and healthy counterparts: the organisation in well aligned stress fibers was disrupted in cancer cell lines and the proteins was mainly concentrated at the periphery of the cell, whereas β-tubulin had a predominantly perinuclear localization. While the F-actin content was lower in cancer cells, particularly Ewing sarcoma (p = 0.018) and Fibrosarcoma (p = 0.023), this effect was even more pronounced in the case of β-tubulin for all cancer-healthy cell duos. Interestingly, chondrosarcoma cells were characterized by a significant upregulation of β-tubulin gene expression (p = 0.005) and protein amount (p = 0.032).

CONCLUSION

Modifications in cellular stiffness, along with structural and compositional cytoskeleton rearrangement, constitute typical features of sarcomas cells, when compared to their healthy counterpart. Notably, whereas a decrease in stiffness is typically a feature of malignant entities, chondrosarcoma cells were stiffer than chondrocytes, with chondrosarcoma cells exhibiting a significantly upregulated β-tubulin expression. Each Sarcoma entity may have his own cellular-stiffness and cytoskeleton organisation/composition fingerprint, which in turn may be exploited for diagnostic or therapeutic purposes.

A novel marker integrating multiple genetic alterations better predicts platinum sensitivity in ovarian cancer than HRD score

Introduction: Platinum-based chemotherapy is the first-line treatment strategy for ovarian cancer patients. The dismal prognosis of ovarian cancer was shown to be stringently associated with the heterogeneity of tumor cells in response to this therapy, therefore understanding platinum sensitivity in ovarian cancer would be helpful for improving patients' quality of life and clinical outcomes. HRDetect, utilized to characterize patients' homologous recombination repair deficiency, was used to predict patients' response to platinum-based chemotherapy. However, whether each of the single features contributing to HRD score is associated with platinum sensitivity remains elusive. Methods: We analyzed the whole-exome sequencing data of 196 patients who received platinum-based chemotherapy from the TCGA database. Genetic features were determined individually to see if they could indicate patients' response to platinum-based chemotherapy and prognosis, then integrated into a Pt-score employing LASSO regression model to assess its predictive performance. Results and discussion: Multiple genetic features, including bi-allelic inactivation of BRCA1/2 genes and genes involved in HR pathway, multiple somatic mutations in genes involved in DNA damage repair (DDR), and previously reported HRD-related features, were found to be stringently associated with platinum sensitivity and improved prognosis. Higher contributions of mutational signature SBS39 or ID6 predicted improved overall survival. Besides, arm-level loss of heterozygosity (LOH) of either chr4p or chr5q predicted significantly better disease-free survival. Notably, some of these features were found independent of HRD. And SBS3, an HRD-related feature, was found irrelevant to platinum sensitivity. Integrated all candidate markers using the LASSO model to yield a Pt-score, which showed better predictive ability compared to HRDetect in determining platinum sensitivity and predicting patients' prognosis, and this performance was validated in an independent cohort. The outcomes of our study will be instrumental in devising effective strategies for treating ovarian cancer with platinum-based chemotherapy.

DDX18 drives tumor immune escape through transcription-activated STAT1 expression in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) resists to current treatments due to its inherent tumor heterogeneity, therapy-resistant cancer stem/initiating cells survival, and immune evasion in the immunosuppressive tumor microenvironment (TME). Here, the results show that clinical PDAC and adjacent tissues undergo distinct chromatin remodeling. Multiple omics analysis revealed DEAD-box RNA helicase 18 (DDX18), a carcinogenic gene with similar H3K4me3 profile, is up-regulated and correlates with poor survival in PDAC patients. We validated that DDX18 deposits on the STAT1 promoter region and counteracts H3K27me3 deposition on the STAT1 promoter sequence by modulating the formation of the PRC2 complex to up-regulate the expression of STAT1, which results in the up-regulation of PD-L1 expression, T lymphocyte accumulation and overactivation in the highly desmoplastic and immunosuppressive pancreatic TME. DDX18-STAT1 axis inhibition also affects stemness of cancer cells, epithelial-mesenchymal transition (EMT) and disrupts the immunosuppressive TME simultaneously, producing sustained remissions of aggressive PDAC by synergizing with anti-PD-L1 therapy. Combining DDX18 inhibition with anti-PD-L1 immunochemotherapy to treat PDAC patients will pave a new way for clinical treatment of patients with PDAC. This study found that clinical PDAC and adjacent pancreatic tissues undergo distinct chromatin remodeling featured by the upregulation of DEAD-box RNA helicase 18 (DDX18). We further validated that DDX18 deposits on the STAT1 promoter region and counteracts H3K27me3 deposition on the STAT1 promoter by modulating the formation of the PRC2 complex to up-regulate the expression of STAT1. DDX18-STAT1 axis enhances the stemness of cancer cells, the upregulation of PD-L1 expression, T lymphocyte accumulation and overactivation in the highly desmoplastic and immunosuppressive pancreatic TME.

Unraveling dynamic interactions between tumor-associated macrophages and consensus molecular subtypes in colorectal cancer: An integrative analysis of single-cell and bulk RNA transcriptome

Background

Accumulating research substantiated that tumor-associated macrophages (TAMs) have a significant impact on the tumorigenesis, progression, and distant metastasis, representing a novel target for various cancers. However, the underlying dynamic changes and interactions between TAMs and tumor cells remain largely elusive in colorectal cancer (CRC).

Methods

We depicted the dynamic changes of macrophages using sing-cell RNA-seq data and extracted TAM differentiation-related genes. Next, we utilized the weighted gene co-expression network analysis (WGCNA) to acquire CMS-related modular genes using bulk RNA-seq data. Finally, we utilized univariate Cox and Lasso Cox regression analyses to identify TAM differentiation-related biomarkers and established a novel risk signature model. We employed quantitative real-time polymerase chain reaction (qRT-PCR) on CRC tissue samples and used immunohistochemistry (IHC) data frome the HPA database to validate the mRNA and protein expression of prognostic genes. The interaction of TAMs and each consensus molecular subtype (CMS) subpopulation was analyzed at the cellular level.

Results

A total of 47,285 cells from single-cell dataset and 1197 CRC patients from bulk dataset were obtained. Among those, 6400 myeloid cells were re-clustered and annotated. RNASE1, F13A1, DAPK1, CLEC10A, RPN2, REG4 and RGS19 were identified as prognostic genes and the risk signature model was established based on the above genes. The qRT-PCR analysis indicated that the expression of RNASE1 and DAPK1 were significantly up-regulated in CRC tumor tissues. The cell-cell communication analysis demonstrated complex interactions between TAMs and CMS malignant cell subpopulations.

Conclusion

This study presents an in-depth dissection of the dynamic features of TAMs in the tumor microenvironment and provides promising therapeutic targets for CRC.

Clonal evolution and hierarchy in myeloid malignancies

Myeloid malignancies, a group of hematopoietic disorders that includes acute myeloid leukemia (AML), myelodysplastic syndromes (MDS), and myeloproliferative neoplasms (MPNs), are caused by the accumulation of genetic and epigenetic changes in hematopoietic stem and progenitor cells (HSPCs) over time. Despite the relatively low number of genomic drivers compared with other forms of cancer, the process by which these changes shape the genomic architecture of myeloid malignancies remains elusive. Recent advancements in clonal hematopoiesis research and the use of cutting-edge single cell technologies have shed new light on the developmental process of myeloid malignancies. In this review, we delve into the intricacies of clonal evolution in myeloid malignancies and its implications for the development of new diagnostic and therapeutic approaches.

Comparison of prognostic value of different metabolic response criteria determined by PET/CT in patients with metastatic breast cancer under CDK 4/6 inhibitor treatment

PURPOSE

This study evaluates the prognostic role of different [18F]FDG PET/CT metabolic response criteria in metastatic breast cancer (MBC) patients treated with cyclin-dependent kinase 4/6 inhibitors (CDK 4/6).

MATERIALS AND METHODS

We retrospectively evaluated the data of MBC patients treated with CDK 4/6 inhibitors who underwent an [18F]FDG PET/CT scan before starting and during treatment. [18F]FDG PET/CT response was assessed with the European Organization for Research and Treatment of Cancer (EORTC), PET Response Criteria in Solid Tumors (PERCIST), and whole-body total lesion glycolysis (WBTLG) criteria. Fleiss kappa was computed to assess the agreement between metabolic response criteria. The endpoint of the study was progression-free survival (PFS). PFS data were analyzed by the Kaplan-Meier method and compared using the log-rank test.

RESULTS

The study included sixteen MBC patients who received CDK 4/6 inhibitors therapy. According to PERCIST, partial metabolic response (PMR) was found in seven patients, stable metabolic disease (SMD) in seven patients, and progressive metabolic disease (PMD) in two patients. According to EORTC, PMR was detected in eight patients, SMD in seven patients, and PMD in one patient. According to WBTLG, PMR was found in 10 patients, SMD in four patients, and PMD in two patients. There was a fair agreement between the three criteria. While progression was detected in seven of the patients during follow-up, no progression was detected in nine of them. Kaplan-Meier analysis revealed that the responders according to WBTLG showed significantly longer PFS than non-responders.

CONCLUSION

Treatment response according to WBTLG criteria during treatment appears to be associated with prolonged PFS in patients treated with CDK 4/6 inhibitors for MBC.

The Efficacy of Nanoparticle Delivery to Hypoxic Solid Tumors by ciRGD Co-Administration Depends on Neuropilin-1 and Neutrophil Levels

The ability to improve nanoparticle delivery to solid tumors is an actively studied domain, where various mechanisms are looked into. In previous work, the authors have looked into nanoparticle size, tumor vessel normalization, and disintegration, and here it is aimed to continue this work by performing an in-depth mechanistic study on the use of ciRGD peptide co-administration. Using a multiparametric approach, it is observed that ciRGD can improve nanoparticle delivery to the tumor itself, but also to tumor cells specifically better than vessel normalization strategies. The effect depends on the level of tumor perfusion, hypoxia, neutrophil levels, and vessel permeability. This work shows that upon characterizing tumors for these parameters, conditions can be selected that can optimally benefit from ciRGD co-administration as a means to improve NP delivery to solid tumors.

Identification of tumor mutations in plasma based on mutation variant frequency change (MVFC)

To overcome the dependency of strategies utilizing cell-free DNA (cfDNA) on tissue sampling, the emergence of sequencing panels for non-invasive mutation screening was promoted. However, cfDNA sequencing with panels still suffers from either inaccuracy or omission, and novel approaches for accurately screening tumor mutations solely based on plasma without gene panel restriction are urgently needed. We performed unique molecular identifier (UMI) target sequencing on plasma samples and peripheral blood mononuclear cells (PBMCs) from 85 hepatocellular carcinoma (HCC) patients receiving surgical resection, which were divided into an exploration dataset (20 patients) or an evaluation dataset (65 patients). Plasma mutations were identified in pre-operative plasma, and the mutation variant frequency change (MVFC) between post- and pre-operative plasma was then calculated. In the exploration dataset, we observed that plasma mutations with MVFC < 0.2 were enriched for tumor mutations identified in tumor tissues and had frequency changes that correlated with tumor burden; these plasma mutations were therefore defined as MVFC-identified tumor mutations. The presence of MVFC-identified tumor mutations after surgery was related to shorter relapse-free survival (RFS) in both datasets and thus indicated minimum residual disease (MRD). The combination of MVFC-identified tumor mutations and Alpha Fetoprotein (AFP) could further improve MRD detection (P < 0.0001). Identification of tumor mutations based on MVFC was also confirmed to be applicable with a different gene panel. Overall, we proposed a novel strategy for non-invasive tumor mutation screening using solely plasma that could be utilized in HCC tumor-burden monitoring and MRD detection.

Proteomic Profiling and Tumor Microenvironment Characterization Reveal Molecular and Immunological Hallmarks of Left-Sided and Right-Sided Colon Cancer Tumorigenesis

Left-sided and right-sided colon cancer (LSCC and RSCC) display different biological and clinical characteristics. However, the differences in their tumorigenesis and tumor microenvironment remain unclear. In this study, we profiled the proteomic landscapes of LSCC and RSCC with data-independent acquisition mass spectrometry (DIA-MS) using fresh tumor and adjacent normal tissues from 24 patients. A total of 7403 proteingroups were primarily identified with DIA-MS. After quality control, 7212 proteingroups were used for further analysis. Through comparing the difference in proteomic profiles between LSCC and RSCC samples, 2556 commonly and 1982 region-type-specific regulated proteingroups were characterized. During the development of LSCC and RSCC, metabolic, growth, cell division, cell adhesion, and migration pathways were found to be significantly dysregulated (P < 0.05), which was further confirmed by transcriptome data from TCGA. Compared to RSCC, most parts of the immune-related signatures, immune cell infiltration scores, and overall immune scores of LSCC were higher. The systematic elucidation of proteomic and transcriptomic profiles in this work improves our understanding of tumorigenesis and immune microenvironment characteristics of LSCC and RSCC.

The screening, identification, design and clinical application of tumor-specific neoantigens for TCR-T cells

Recent advances in neoantigen research have accelerated the development of tumor immunotherapies, including adoptive cell therapies (ACTs), cancer vaccines and antibody-based therapies, particularly for solid tumors. With the development of next-generation sequencing and bioinformatics technology, the rapid identification and prediction of tumor-specific antigens (TSAs) has become possible. Compared with tumor-associated antigens (TAAs), highly immunogenic TSAs provide new targets for personalized tumor immunotherapy and can be used as prospective indicators for predicting tumor patient survival, prognosis, and immune checkpoint blockade response. Here, the identification and characterization of neoantigens and the clinical application of neoantigen-based TCR-T immunotherapy strategies are summarized, and the current status, inherent challenges, and clinical translational potential of these strategies are discussed.

From Chaos to Opportunity: Decoding Cancer Heterogeneity for Enhanced Treatment Strategies

Cancer manifests as a multifaceted disease, characterized by aberrant cellular proliferation, survival, migration, and invasion. Tumors exhibit variances across diverse dimensions, encompassing genetic, epigenetic, and transcriptional realms. This heterogeneity poses significant challenges in prognosis and treatment, affording tumors advantages through an increased propensity to accumulate mutations linked to immune system evasion and drug resistance. In this review, we offer insights into tumor heterogeneity as a crucial characteristic of cancer, exploring the difficulties associated with measuring and quantifying such heterogeneity from clinical and biological perspectives. By emphasizing the critical nature of understanding tumor heterogeneity, this work contributes to raising awareness about the importance of developing effective cancer therapies that target this distinct and elusive trait of cancer.

Padlock Probe-Based Targeted In Situ Sequencing: Overview of Methods and Applications

Elucidating spatiotemporal changes in gene expression has been an essential goal in studies of health, development, and disease. In the emerging field of spatially resolved transcriptomics, gene expression profiles are acquired with the tissue architecture maintained, sometimes at cellular resolution. This has allowed for the development of spatial cell atlases, studies of cell-cell interactions, and in situ cell typing. In this review, we focus on padlock probe-based in situ sequencing, which is a targeted spatially resolved transcriptomic method. We summarize recent methodological and computational tool developments and discuss key applications. We also discuss compatibility with other methods and integration with multiomic platforms for future applications.

Metabolic heterogeneity in adrenocortical carcinoma impacts patient outcomes

Spatially resolved metabolomics enables the investigation of tumoral metabolites in situ. Inter- and intratumor heterogeneity are key factors associated with patient outcomes. Adrenocortical carcinoma (ACC) is an exceedingly rare tumor associated with poor survival. Its clinical prognosis is highly variable, but the contributions of tumor metabolic heterogeneity have not been investigated thus far to our knowledge. An in-depth understanding of tumor heterogeneity requires molecular feature-based identification of tumor subpopulations associated with tumor aggressiveness. Here, using spatial metabolomics by high-mass resolution MALDI Fourier transform ion cyclotron resonance mass spectrometry imaging, we assessed metabolic heterogeneity by de novo discovery of metabolic subpopulations and Simpson's diversity index. After identification of tumor subpopulations in 72 patients with ACC, we additionally performed a comparison with 25 tissue sections of normal adrenal cortex to identify their common and unique metabolic subpopulations. We observed variability of ACC tumor heterogeneity and correlation of high metabolic heterogeneity with worse clinical outcome. Moreover, we identified tumor subpopulations that served as independent prognostic factors and, furthermore, discovered 4 associated anticancer drug action pathways. Our research may facilitate comprehensive understanding of the biological implications of tumor subpopulations in ACC and showed that metabolic heterogeneity might impact chemotherapy.

Advancing Breast Cancer Heterogeneity Analysis: Insights from Genomics, Transcriptomics and Proteomics at Bulk and Single-Cell Levels

Breast cancer continues to pose a significant healthcare challenge worldwide for its inherent molecular heterogeneity. This review offers an in-depth assessment of the molecular profiling undertaken to understand this heterogeneity, focusing on multi-omics strategies applied both in traditional bulk and single-cell levels. Genomic investigations have profoundly informed our comprehension of breast cancer, enabling its categorization into six intrinsic molecular subtypes. Beyond genomics, transcriptomics has rendered deeper insights into the gene expression landscape of breast cancer cells. It has also facilitated the formulation of more precise predictive and prognostic models, thereby enriching the field of personalized medicine in breast cancer. The comparison between traditional and single-cell transcriptomics has identified unique gene expression patterns and facilitated the understanding of cell-to-cell variability. Proteomics provides further insights into breast cancer subtypes by illuminating intricate protein expression patterns and their post-translational modifications. The adoption of single-cell proteomics has been instrumental in this regard, revealing the complex dynamics of protein regulation and interaction. Despite these advancements, this review underscores the need for a holistic integration of multiple 'omics' strategies to fully decipher breast cancer heterogeneity. Such integration not only ensures a comprehensive understanding of breast cancer's molecular complexities, but also promotes the development of personalized treatment strategies.