Spatial transcriptomics is a powerful method for studying the spatial organization of cells, which is a critical feature in the development, function and evolution of multicellular life. However, sequencing-based spatial transcriptomics has not yet achieved cellular-level resolution, so advanced deconvolution methods are needed to infer cell-type contributions at each location in the data. Recent progress has led to diverse tools for cell-type deconvolution that are helping to describe tissue architectures in health and disease. In this Review, we describe the varied types of cell-type deconvolution methods for spatial transcriptomics, contrast their capabilities and summarize them in a web-based, interactive table to enable more efficient method selection.

3D cellular-specific epigenetic and transcriptomic reprogramming is critical to organogenesis and tumorigenesis. Here, we dissect the distinct cell fitness in 2D (normoxia vs. chronic hypoxia) vs 3D (normoxia) culture conditions for an MYC-driven murine liver cancer model. We identify over 600 shared essential genes and additional context-specific fitness genes and pathways. Knockout of the VHL-HIF1 pathway results in incompatible fitness defects under normoxia vs. 1% oxygen or 3D culture conditions. Moreover, deletion of each of the mitochondrial respiratory electron transport chain complex has distinct fitness outcomes. Notably, multicellular organogenesis signaling pathways including TGFβ-SMAD, which is upregulated in 3D culture, specifically constrict the uncontrolled cell proliferation in 3D while inactivation of epigenetic modifiers (Bcor, Kmt2d, Mettl3, and Mettl14) has opposite outcomes in 2D vs. 3D. We further identify a 3D-dependent synthetic lethality with partial loss of Prmt5 due to a reduction of Mtap expression resulting from 3D-specific epigenetic reprogramming. Our study highlights unique epigenetic, metabolic, and organogenesis signaling dependencies under different cellular settings.

As the end-product of glycolysis, lactate serves as a regulator of protein lactylation in addition to being an energy substrate, metabolite, and signaling molecule in cancer. The reprogramming of glucose metabolism and the Warburg effect in breast cancer results in extensive lactate production and accumulation, making it likely that lactylation in tumor tissue is also abnormal. This review summarizes evidence on lactylation derived from studies of lactate metabolism and disease, highlighting the role of lactate in the tumor microenvironment of breast cancer and detailing the levels of lactylation and cancer-promoting mechanisms across various tumors. The roles of lactate and lactylation, along with potential intervention mechanisms, are presented and discussed, offering valuable insights for future research on the role of lactylation in tumors.

Chemotherapy remains a prevalent strategy in cancer therapy; however, the emergence of drug resistance poses a considerable challenge to its efficacy. Most drug resistance arises from the accumulation of genetic mutations in a minority of resistant cells. The mechanisms underlying the emergence and progression of cancer resistance from these minority-resistant cells (MRCs) remain poorly understood. This study employs force-induced remnant magnetization spectroscopy (FIRMS) alongside various biological investigations to reveal the mechanical pathways for MRCs fostering drug resistance and tumor progression. The findings show that minority Paclitaxel-resistant cancer cells have enhanced mechanical properties. These cells can transmit high-intensity forces to surrounding sensitive cells (SCs) through the force transducer, Merlin. This force transmission facilitates the assimilation of surrounding SCs, subsequently strengthening the contraction and adhesion of tumor cells. This process is termed "mechano-assimilation," which accelerates the development of drug resistance and tumor progression. Interestingly, disturbances and reductions of mechano-assimilation within tumors can restore sensitivity to Paclitaxel both in vitro and in vivo. This study provides preliminary evidence highlighting the contribution of MRCs to the development of drug resistance and malignancy, mediated through mechanical interactions. It also establishes a foundation for future research focused on integrating mechanical factors into innovative cancer therapies.

Would transcriptomes change if cell collectives acquired a novel morphogenetic and behavioral phenotype in the absence of genomic editing, transgenes, heterologous materials, or drugs? We investigate the effects of morphology and nascent emergent life history on gene expression in the basal (no engineering, no sculpting) form of Xenobots -autonomously motile constructs derived from Xenopus embryo ectodermal cell explants. To investigate gene expression differences between cells in the context of an embryo with those that have been freed from instructive signals and acquired novel lived experiences, we compare transcriptomes of these basal Xenobots with age-matched Xenopus embryos. Basal Xenobots show significantly larger inter-individual gene variability than age-matched embryos, suggesting increased exploration of the transcriptional space. We identify at least 537 (non-epidermal) transcripts uniquely upregulated in these Xenobots. Phylostratigraphy shows a majority of transcriptomic shifts in the basal Xenobots towards evolutionarily ancient transcripts. Pathway analyses indicate transcriptomic shifts in the categories of motility machinery, multicellularity, stress and immune response, metabolism, thanatotranscriptome, and sensory perception of sound and mechanical stimuli. We experimentally confirm that basal Xenobots respond to acoustic stimuli via changes in behavior. Together, these data may have implications for evolution, biomedicine, and synthetic morphoengineering.

Magneto-acousto electrical tomography (MAET) is a novel medical imaging technique that relies on the difference in electrical properties between healthy and tumor tissues. To facilitate MAET experiments, this study proposes a comprehensive procedure for developing, characterizing, and preserving realistic breast tissue-mimicking phantoms. We developed nontoxic and inexpensive phantoms using sodium alginate, graphite powder, agar, propanediol, aluminum powder, glycine, and deionized water. The dielectric (conductivity and permittivity) and acoustic (speed of sound) properties of phantoms (breast fat, breast gland, and tumor) within the 1-8 MHz frequency range were measured to ensure their suitability for MAET experiments. In conclusion, this study presents a detailed methodology for the preparation, characterization, and preservation of realistic breast tissue-mimicking phantoms tailored for MAET experiments.

Mutp53 level is widely variable among individual cancer cells in tumor tissues, and within cells a higher level of mutp53 is usually observed in the nucleus as compared to the cytoplasm. This spatial heterogeneity in mutp53 expression has been well documented and likely plays an important role in tumor therapeutic resistance. However, its underlying mechanism remains poorly understood. In this study, we first revealed a critical role of micro-environmental reducing status in regulating mutp53 stability and spatially heterogeneous accumulation. Immunofluorescence and ThiolTracker Violet dye staining demonstrated a clear correlation between the cellular mutp53 level and the reducibility in the patient-derived tumor tissues and mutp53-expressing cancer cell lines. The nucleus exhibited both higher reducibility and more mutp53 accumulation than the cytoplasm did. Supplementing GSH exacerbated the accumulation of mutp53, while consuming GSH led to extensive depletion of mutp53, suggesting that the environmental reducing status kept mutp53 stability. Mechanistically, S-glutathionylation could trigger ubiquitination and proteasomal degradation of mutp53. A highly-reducing local environment preserved mutp53 stability by inhibiting glutathionylation and subsequent proteasomal degradation of mutp53, which also provided an explanation for the differential accumulation of mutp53 proteins in the nucleus and cytoplasm. Thirdly, we revealed that the expression level of glutathione reductase (GR) was positively correlated with mutp53 accumulation across the cultured mutp53-expressing cell lines, patient-derived tumor tissues and patient databases. Over-expression of GR reinforced the environmental reducibility, affected glutathionylation and improved mutp53 accumulation, while inhibiting GR either by chemical inhibitors or genetic approach induced massive clearance of a variety of mutp53 and effectively retarded the growth of p53-mutated cell-derived xenografts in mice. These studies provided an explanation for the widely-observed spatial heterogeneous accumulation of mutp53 proteins, and inhibiting GR or directly consuming GSH represented a promising strategy for mutp53 carrying cancer therapy.

Epigenomic mechanisms are critically involved in mediation of genetic and environmental factors that underlie cancer development. Histone modifications represent highly informative epigenomic marks that reveal activation and repression of gene activities and dysregulation of transcriptional control due to tumorigenesis. Here, we present a comprehensive epigenomic and transcriptomic mapping of 18 stage I and II tumor and 20 non-neoplastic tissues from non-small cell lung adenocarcinoma patients. Our profiling covers 5 histone marks including activating (H3K4me3, H3K4me1, and H3K27ac) and repressive (H3K27me3 and H3K9me3) marks and the transcriptome using only 20 mg of tissue per sample, enabled by low-input omic technologies. Using advanced integrative bioinformatic analysis, we uncover cancer-driving signaling cascade networks, changes in 3D genome modularity, differential expression and functionalities of transcription factors and noncoding RNAs. Many of these identified genes and regulatory molecules show no significant change in their expression or a single epigenomic modality, emphasizing the power of integrative multimodal and multiomic analysis using patient samples.

Non-small cell lung cancer (NSCLC) accounts for 80% of lung cancers, the leading cause of cancer mortality. microRNAs (miRNA, miR) have emerged as important components of carcinogenesis and promising biomarkers. We aimed to analyse global plasma miRs in NSCLC patients before and at least one year after tumour resection.

Plasma was collected from the peripheral blood of 24 donors without cancer and of NSCLC patients before surgery (n=36) and at least 1 year after surgery (n=12). Next-generation sequencing (NGS)-based miR profiling was performed. Patients were followed-up for 4 to 12 years after surgery to assess disease recurrence.

Untreated NSCLC patients exhibited significant changes in plasma miR levels compared to cancer-free donors (48 up- and 17 down-regulated miRs). miR profiles in patients with adenocarcinoma (ADC) (n=18) and squamous cell carcinoma (SCC) significantly differed (16 and 86 miRs up-, and 15 and 16 miRs down-regulated, respectively). A subset of pre-surgery deregulated miRs was found to be associated with recurrence (49 miRs). Six miRs were shown to have independent prognostic value. After tumour resection, some pre-surgery miR alterations returned to control levels (18 miRs), some others persisted (27 miRs), while also novel plasma miR changes emerged (75 miRs) in patients with no clinical evidence of recurrence.

Untreated NSCLC patients present deregulated plasma miRs, some of which may have a potential of prognostic markers. After tumour excision plasma miR profiles change, some miR levels normalise, some changes persist and novel miR changes are observed despite no clinical symptoms of recurrence. Plasma miR profiles in NSCLC patients may suggest systemic abnormalities predisposing to lung cancer and/or reflect a systemic response to pre-cancer/dormant cancer cells.

Three-dimensional (3D) optical microscopy permits in situ interrogation of the tumor microenvironment (TME) in volumetric tumors for research while light sheet and confocal fluorescence microscopy are often used to achieve macroscopic and microscopic 3D images of tissues, respectively. Although each technique offers distinct fields of view (FOVs) and spatial resolution, the combination of the two to obtain correlative multiscale 3D images from the same tumor tissues has not yet been explored. We established a workflow that enables the tracking and 3D imaging of region of interests (ROIs) within tumor tissues through sequential light sheet and confocal fluorescence microscopy. This approach allowed for quantitative 3D spatial analysis of the immune response in the TME at multiple spatial scales and facilitated the direct localization of a metastatic lesion within a mouse brain. Our method offers an approach for correlative multiscale 3D optical microscopy with the potential to provide new insights into comprehensive research in disease mechanism or drug response.

Fibroinflammation refers to the highly integrated fibrogenic and inflammatory responses mediated by the concerted function of fibroblasts and innate immune cells in response to tissue perturbation. This process underlies the desmoplastic remodelling of the tumour microenvironment and thus plays an important role in tumour initiation, growth and metastasis. More specifically, fibroinflammation alters the biochemical and biomechanical signalling in malignant cells to promote their proliferation and survival and further supports an immunosuppressive microenvironment by polarizing the immune status of tumours. Additionally, the presence of fibroinflammation is often associated with therapeutic resistance. As such, there is increasing interest in targeting this process to normalize the tumour microenvironment and thus enhance the treatment of solid tumours. Herein, we review advances made in unravelling the complexity of cancer-associated fibroinflammation that can inform the rational design of therapies targeting this.

Breast cancer (BC) is the most common type of cancer in women worldwide. Solid tumors are complex structures composed of many cell types and extracellular matrix components. Understanding solid tumors is crucial for developing effective treatments. This study aimed to develop a gene expression classifier to predict BC with high accuracy. The study first identified the most important genes for cancer through differential expression analysis (DEA) between breast cancer and adjacent normal breast samples. The R package STRINGdb was then used to create a protein-protein interaction network (PPI) to examine upregulated genes and find clusters. Enrichment analyses were performed to identify overrepresented biological functions and pathways. A logistic regression prediction model was developed using a breast cancer dataset from TCGA and evaluated using discrimination and calibration measures. BUB1 expression in breast cancer was also investigated using quantitative analysis. Two significant clusters were identified, with cell cycle checkpoints and M phase key pathways in one cluster and extracellular matrix organization in the other. A prediction model using the hub gene set (COMP, FN1, SDC1, BUB1, TTK, and NUSAP1) showed high sensitivity (97.2%) and specificity (96.1%), and an AUC of 0.994. Three hub genes (COMP, FN1, and SDC1) were identified through the PPI network, strongly linked to extracellular matrix organization (BUB1, TTK, and NUSAP1) as hub genes involved in M phase and cell cycle checkpoints. Overall, the study identified hub pathways and genes that accurately distinguish between cancer and normal samples, presenting promising new possibilities for early cancer detection and improved BC therapy.

Genome-wide functional genetic screening has been widely used in the biomedicine field, which makes it possible to find a needle in a haystack at the genetic level. In cancer research, gene mutations are closely related to tumor development, metastasis, and recurrence, and the use of state-of-the-art powerful screening technologies, such as clustered regularly interspaced short palindromic repeat (CRISPR), to search for the most critical genes or coding products provides us with a new possibility to further refine the cancer mapping and provide new possibilities for the treatment of cancer patients. The use of CRISPR screening for the most critical genes or coding products has further refined the cancer atlas and provided new possibilities for the treatment of cancer patients. Immunotherapy, as a highly promising cancer treatment method, has been widely validated in the clinic, but it could only meet the needs of a small proportion of cancer patients. Finding new immunotherapy targets is the key to the future of tumor immunotherapy. Here, we revisit the application of functional screening in cancer immunology from different perspectives, from the selection of diverse in vitro and in vivo screening models to the screening of potential immune checkpoints and potentiating genes for CAR-T cells. The data will offer fresh therapeutic clues for cancer patients.

Comprehensive genomic profiling (CGP) testing is used worldwide for personalized cancer treatment. Unstained slides from formalin-fixed paraffin-embedded (FFPE) blocks are required for tissue-based CGP testing. However, the use of low quality FFPE specimens can result in testing failure or invalid results. Although several previous studies have indicated that the quality of genomic testing is affected by various factors, the factor(s) that has the greatest influence on CGP testing has not been well studied in real-world data. Thus, we conducted a large-scale multi-institutional study in Hiroshima, Japan to investigate the factors associated with quality check status in FoundationOne CDx CGP testing using real-world data from 1,204 participants from an area with a population of approximately 2.7 million. This study revealed low percentage of tumor nuclei in FFPE specimen, long-term storage of FFPE block, and pancreatic cancer as independent risk factors for qualified status. Of the three factors, percentage of tumor nuclei had the largest effect on quality check status, while the magnitudes of the effects of storage time of FFPE or pancreatic cancer were minor. Collectively, our real-world data indicate that tumor purity is the most important factor for successful CGP, and we would suggest greater than 35% as an ideal percentage of tumor nuclei for CGP submission.

Nanotechnology is a significant factor that has assisted researchers in overcoming medications' permeability and retention effects. This article discusses how different nanoparticles, such as metallic nanoparticles, carbon nanotubes (CNTs), and extracellular vesicles (EVs), are transforming cancer treatments and diagnosis. While CNTs provide photothermal qualities that enable synergistic effects when paired with chemotherapy, EVs provide biocompatibility and immune evasion, enabling effective drug transport. Because of their special optical and magnetic characteristics, metallic nanoparticles are essential for imaging and targeted medication administration. When compared to traditional treatments, these nanoparticles improve bioavailability, decrease systemic toxicity, and increase therapeutic efficacy. Despite increased investigations, the number of licensed nano-drugs has remained relatively high. More investigation is required into targeted drug delivery using nanocarriers to minimize the shielding impact of the protein corona, increase permeability and retention effects, and reduce toxicity to improve clinical translation. This study focuses on novel approaches and state-of-the-art cancer therapies using nanoparticles that target different cancer cells. It also emphasized the advantages of nanoparticle-based cancer therapies over conventional ones, their difficulties, and future promises.

Oncological diseases consistently occupy leading positions among the most life-threatening diseases, including in highly developed countries. At the same time, the second most common cause of cancer death is colorectal cancer. The current level of research shows that the development of effective therapy, in this case, requires a new grade of understanding processes during the emergence and development of a tumor. In particular, the concept of cancer stem cells that ensure the survival of chemoresistant cells capable of giving rise to new tumors is becoming widespread. To provide adequate conditions that reproduce natural processes typical for tumor development, approaches based on increasingly complex cellular systems are being improved. This review discusses the main strategies that allow for the study of the properties of tumor cells with an emphasis on colorectal cancer stem cells. The features of working with tumor cells and the advantages and disadvantages of 2D and 3D culture systems are considered.

Deepening our understanding of neuro-cancer interactions can innovate brain tumor treatment. This mini review unfolds the most relevant and recent insights into the neural mechanisms contributing to brain tumor initiation, progression, and resistance, including synaptic connections between neurons and cancer cells, paracrine neuro-cancer signaling, and cancer cells' intrinsic neural properties. We explain the basic and clinical-translational relevance of these findings, identify unresolved questions and particularly interesting future research avenues, such as central nervous system neuro-immunooncology, and discuss the potential transferability to extracranial cancers. Lastly, we conceptualize ways toward clinical trials and develop a roadmap toward neuroscience-instructed brain tumor therapies. Significance: Neural influences on brain tumors drive their growth and invasion. Herein, we develop a roadmap to use these fundamentally new insights into brain tumor biology for improved outcomes.

An optimal amount of labile zinc (Zn 2+ ) is essential for proliferation of human cells, where Zn 2+ levels that are too high or too low cause cell cycle exit. Tumors of the breast have been characterized by high levels of total Zn 2+ . Given the role of Zn 2+ in proliferation of human cells and elevation of zinc in breast cancer tumors, we examined the concentration of total and labile Zn 2+ across a panel of 5 breast cancer cell lines, compared to the normal MCF10A cell line. We found that three cell lines (MDA-MB-231, MDA-MB-157, and SK-Br-3) showed elevated labile Zn 2+ in the cytosol, while T-47D showed significantly lower Zn 2+ , and MCF7 showed no change compared to MCF10A cells. There was no change in total Zn 2+ across the cell lines, as measured by ICP-MS, but we did observe a difference in the cells ability to accumulate Zn 2+ when Zn 2+ in the media was elevated. Therefore, we examined how proliferation of each cell line was affected by increases and decreases in the media. We found striking differences, where three cancer cell lines (MDA-MB-231, MDA-MB-157, and MCF7) showed robust proliferation in high Zn 2+ at concentrations that killed MCF10A, T-47D, and SK-Br-3 cells. We also discovered that 4 of the 5 cancer cell lines demonstrate compromised proliferation and increased cell death in low Zn 2+ , suggesting these cells may be addicted to Zn 2+ . Overall, our study suggests significant differences in Zn 2+ homeostasis and regulation in different types of breast cancer cells, with consequences for both proliferation and cell viability.

Respiratory diseases such as asthma, acute respiratory distress syndrome (ARDS), influenza or COVID-19 often directly target the epithelium. Elevated immune levels and a 'cytokine storm' are directly associated with defective healing dynamics of lung diseases such as COVID-19 or ARDS. The infected cells leave wounded regions in the epithelium which must be healed for the lung to return to a healthy state and carry out its main function of gas-exchange. Due to the complexity of the various interactions between cells of the lung epithelium and surrounding tissue, it is necessary to develop models that can complement experiments to fully understand the healing dynamics. In this mathematical study we model the mechanism of epithelial regeneration. We assume that healing is exclusively driven by progenitor cell proliferation, induced by a chemical activator such as epithelial growth factor (EGF) and cytokines such as interleukin-22 (IL22). Contrary to previous studies of wound healing, we consider the immune system, specifically the T effector cells TH1, TH17, TH22 and Treg to strongly contribute to the healing process, by producing IL22 or regulating the immune response. We therefore obtain a coupled system of two ordinary differential equations for the epithelial and immune cell densities and two functions for the levels of chemicals that either induce epithelial proliferation or recruit immune cells. These functions link the two cell equations. We find that to allow the epithelium to regenerate to a healthy state, the immune system must not exceed a threshold value at the onset of the healing phase. This immune threshold is supported experimentally but was not explicitly built into our equations. Our assumptions are therefore sufficient to reproduce experimental results concerning the ratio TH17/Treg cells as a threshold to predict higher mortality rates in patients. This immune threshold can be controlled by parameters of the model, specifically the base-level growth factor concentration. This conclusion is based on a mathematical bifurcation analysis and linearization of the model equations. Our results suggest treatment of severe cases of lung injury by reducing or suppressing the immune response, in an individual patient, assessed by their disease parameters such as course of lung injury and immune response levels.

3D cellular-specific epigenetic and transcriptomic reprogramming is critical to organogenesis and tumorigenesis. Here we dissect the distinct cell fitness in 2D (normoxia vs. chronic hypoxia) vs 3D (normoxia) culture conditions for a MYC-driven murine liver cancer model. We identify over 600 shared essential genes and additional context-specific fitness genes and pathways. Knockout of the VHL-HIF1 pathway results in incompatible fitness defects under normoxia vs. 1% oxygen or 3D culture conditions. Moreover, deletion of each of the mitochondrial respiratory electron transport chain complex has distinct fitness outcomes. Notably, multicellular organogenesis signaling pathways including TGFb-SMAD, which is upregulated in 3D culture, specifically constrict the uncontrolled cell proliferation in 3D while inactivation of epigenetic modifiers (Bcor, Kmt2d, METTL3 and METTL14) has opposite outcomes in 2D vs. 3D. We further identify a 3D-dependent synthetic lethality with partial loss of Prmt5 due to a reduction of Mtap expression resulting from 3D-specific epigenetic reprogramming. Our study highlights unique epigenetic, metabolic and organogenesis signaling dependencies under different cellular settings.

Cancers during oncogenic progression hold information in epigenetic memory which allows flexible encoding of malignant phenotypes and more rapid reaction to the environment when compared to purely mutation-based clonal evolution mechanisms. Cancer memory describes a proposed mechanism by which complex information such as metastasis phenotypes, therapy resistance and interaction patterns with the tumor environment might be encoded at multiple levels via mechanisms used in memory formation in the brain and immune system (e.g. single-cell epigenetic changes and distributed state modifications in cellular ensembles). Carcinogenesis might hence be the result of physiological multi-level learning mechanisms unleashed by defined heritable oncogenic changes which lead to tumor-specific loss of goal state integration into the whole organism. The formation of cancer memories would create and bind new levels of individuality within the host organism into the entity we call cancer. Translational implications of cancer memory are that cancers could be engaged at higher organizational levels (e.g. be "trained" for memory extinction) and that compounds that are known to interfere with memory processes could be investigated for their potential to block cancer memory formation or recall. It also suggests that diagnostic measures should extend beyond sequencing approaches to functional diagnosis of cancer physiology.

Despite remarkable progress in basic oncology, practical results remain unsatisfactory. This discrepancy is partly due to the exclusive focus on processes within the cancer cell, which results in a lack of recognition of cancer as a systemic disease. It is evident that a wise balance is needed between two alternative methodological approaches: reductionism, which would break down complex phenomena into smaller units to be studied separately, and holism, which emphasizes the study of complex systems as integrated wholes. A consistent holistic approach has so far led to the notion of cancer as a special organ, stimulating debate about its function and evolutionary significance. This article discusses the role of cancer as a mechanism of purifying selection of the gene pool, the correlation between hereditary and sporadic cancer, the cancer interactome, and the role of metastasis in a lethal outcome. It is also proposed that neutralizing the cancer interactome may be a novel treatment strategy.

To evaluate the predictive utility of N6-methyladenosine (m6A)-associated long non-coding RNAs (lncRNAs) for the prognosis and immunotherapy response in papillary renal cell carcinoma (pRCC). Transcriptomic data of pRCC samples were extracted from the TCGA database. The m6A-related lncRNAs were identified by Pearson correlation analysis. Univariate and LASSO regression analyses were used to develop a risk model. The discrimination and predictive ability were evaluated through survival analysis, ROC analysis and consensus clustering. Tumor mutation burden (TMB) and immune infiltration of the risk groups were compared. A prognostic nomogram was constructed using six m6A-related lncRNAs, and validated through calibration and decision curve analysis (DCA). The lncRNAs HCG25 and NOP14-AS1 were knocked down in a human pRCC cell line using specific siRNA constructs, and the proliferation and migration rates were assessed by the CCK-8 and transwell assays. We identified a total of 153 m6A-related lncRNAs in pRCC datasets, of which six were selected for constructing a m6A-related lncRNA pRCC prognostic model. Mutations in the SETD2 gene correlated with worse prognosis. Significant differences were observed in immune cell infiltration between the two risk groups. A clinical prognostic nomogram for pRCC was further established based on clinical variables. In vitro assays further showed that HCG25 and NOP14-AS1 regulate the proliferation and migration of pRCC cells. The results validated the discrimination ability of both the m6A-related lncRNA pRCC prognostic model and the pRCC clinical prognostic nomogram. We developed a clinical prognostic nomogram for pRCC using pRCC prognostic-associated m6A-related lncRNAs, which can be utilized for predicting the prognosis and immune landscape of pRCC patients.

Multiplexed imaging technologies provide crucial insights into interactions between tumors and their surrounding tumor microenvironment (TME), but their widespread adoption is limited by cost, time, and tissue availability. We introduce HistoPlexer, a deep learning (DL) framework that generates spatially-resolved protein multiplexes directly from histopathology images. HistoPlexer employs the conditional generative adversarial networks with custom loss functions that mitigate slice-to-slice variations and preserve spatial protein correlations. In a comprehensive evaluation on metastatic melanoma samples, HistoPlexer consistently outperforms existing approaches, achieving superior Multiscale Structural Similarity Index and Peak Signal-to-Noise Ratio. Qualitative evaluation by domain experts demonstrates that the generated protein multiplexes closely resemble the real ones, evidenced by Human Eye Perceptual Evaluation error rates exceeding the 50% threshold for perceived realism. Importantly, HistoPlexer preserves crucial biological relationships, accurately capturing spatial co-localization patterns among proteins. In addition, the spatial distribution of cell types derived from HistoPlexer-generated protein multiplex enables effective stratification of tumors into immune hot versus cold subtypes. When applied to an independent cohort, incorporating additional features from HistoPlexer-generated multiplexes enhances the performance of the DL model for survival prediction and immune subtyping, outperforming the model reliant solely on Hematoxylin & Eosin (H&E) image features. By enabling the generation of whole-slide protein multiplex from the H&E image, HistoPlexer offers a cost- and time-effective approach to understanding the TME, and holds promise for advancing precision oncology.

Tumor metastasis is a complex phenomenon that poses significant challenges to current cancer therapeutics. While the biochemical signaling involved in promoting motile phenotypes is well understood, the role of biomechanical interactions has recently begun to be incorporated into models of tumor cell migration. Specifically, we propose the unjamming transition, adapted from physical paradigms describing the behavior of granular materials, to better discern the transition toward an invasive phenotype. In this review, we introduce the jamming transition broadly and narrow our discussion to the different modes of 3D tumor cell migration that arise. Then we discuss the mechanical interactions between tumor cells and their neighbors, along with the interactions between tumor cells and the surrounding extracellular matrix. We center our discussion on the interactions that induce a motile state or unjamming transition in these contexts. By considering the interplay between biochemical and biomechanical signaling in tumor cell migration, we can advance our understanding of biomechanical control in cancer metastasis.

The pervasiveness of cancer is a global health concern posing a major threat in terms of mortality and incidence rates. Magnetic hyperthermia (MHT) employing biocompatible magnetic nanoparticles (MNPs) ensuring selective attachment to target sites, better colloidal stability and conserving nearby healthy tissues has garnered widespread acceptance as a promising clinical treatment for cancer cell death. In this direction, multifunctional iron oxide nanoparticles (IONPs) are of significant interest for improved cancer care due to finite size effect associated with inherent magnetic properties. This review offers a comprehensive perception of IONPs-mediated MHT from fundamentals to clinical translation, by elucidating the underlying mechanism of heat generation and the related influential factors. Biological mechanisms underlying MHT-mediated cancer cell death such as reactive oxygen species generation and lysosomal membrane permeabilization have been discussed in this review. Recent advances in biological interactions (in vitro and in vivo) of IONPs and their translation to clinical MHT applications are briefed. New frontiers and prospects of promising combination cancer therapies such as MHT with photothermal therapy, cancer starvation therapy and sonodynamic therapy are presented in detail. Finally, this review concludes by addressing current crucial challenges and proposing possible solutions to achieve clinical success.

3D printing has emerged as a powerful tool demonstrating effectiveness in early screening and targeted delivery for various types of tumors. Although the applications of additive manufacturing for cancer are widespread, the issues of scaling up, quality control and specificity remain. This review presents a comprehensive analysis of the current landscape of use of additive manufacturing in cancer diagnostics and treatment. Furthermore, it proceeds to elucidate the prominent current and future applications of 4D- and 5D-printed micro-swimmers in cancer treatment with particular emphasis on the significant progress made in magnetic, biological and light-based propulsion microrobots. Lastly, the current limitations and future research directions are enumerated. In summary, this paper serves as a comprehensive exploration of the remarkable contributions of additive manufacturing to the diagnosis and treatment of cancer.

The intratumoral microbiome (ITM) is in the spotlight due to its possible contribution to the initiation, progression, and invasion of a wide range of cancers. Its precise contribution to cancer tumorigenesis is still elusive, though. Thyroid cancer(TC), the ninth leading cause of cancer globally and the most prevalent endocrine malignancy with a rapidly rising incidence among all cancers, has attracted much attention nowadays. Still, the association between the tumor's microbiome and TC progression and development is an evolving area of investigation with significant consequences for disease understanding and intervention. Therefore, this review offers an appropriate perspective on this emerging concept in TC based on prior studies on the ITM among the most common tumors worldwide, concentrating on TC. Moreover, information on the origin of the ITM and practical methods can pave the way for researchers to opt for the most appropriate method for further investigations on the ITM more accurately.

Wound healing represents a complex and evolutionarily conserved process across vertebrates, encompassing a series of life-rescuing events. The healing process runs in three main phases: inflammation, proliferation, and maturation/remodelling. While acute inflammation is indispensable for cleansing the wound, removing infection, and eliminating dead tissue characterised by the prevalence of neutrophils, the proliferation phase is characterised by transition into the inflammatory cell profile, shifting towards the prevalence of macrophages. The proliferation phase involves development of granulation tissue, comprising fibroblasts, activated myofibroblasts, and inflammatory and endothelial cells. Communication among these cellular components occurs through intercellular contacts, extracellular matrix secretion, as well as paracrine production of bioactive factors and proteolytic enzymes. The proliferation phase of healing is intricately regulated by inflammation, particularly interleukin-6. Prolonged inflammation results in dysregulations during the granulation tissue formation and may lead to the development of chronic wounds or hypertrophic/keloid scars. Notably, pathological processes such as autoimmune chronic inflammation, organ fibrosis, the tumour microenvironment, and impaired repair following viral infections notably share morphological and functional similarities with granulation tissue. Consequently, wound healing emerges as a prototype for understanding these diverse pathological processes. The prospect of gaining a comprehensive understanding of wound healing holds the potential to furnish fundamental insights into modulation of the intricate dialogue between cancer cells and non-cancer cells within the cancer ecosystem. This knowledge may pave the way for innovative approaches to cancer diagnostics, disease monitoring, and anticancer therapy.

Over the past decade, chimeric antigen receptor (CAR)-T cell therapy has emerged as a revolutionary immunotherapeutic approach to combat cancer. This therapy constructs a CAR on the surface of T cells through genetic engineering techniques. The CAR is formed from a combination of antibody-derived or ligand-derived domains and T-cell receptor (TCR) domains. This enables T cells to specifically bind to and activate against tumor cells. However, the efficacy of CAR-T cells in solid tumors remains inconclusive due to several challenges such as poor tumor trafficking, infiltration, and the immunosuppressive tumor microenvironment (TME). In response, CAR natural killer (CAR-NK) and CAR macrophages (CAR-M) have been developed as complementary strategies for solid tumors. CAR-NK cells do not require HLA compatibility, demonstrate reduced toxicity, and are thus seen as potential substitutes for CAR-T cells. Furthermore, CAR-M immunotherapy is also being researched and has shown phagocytic capabilities and tumor-antigen presentation. This study discusses the features, advantages, and limitations of CAR-T, CAR-NK, and CAR-M cells in the treatment of solid tumors and suggests prospective solutions for enhancing the efficacy of CAR host-cell-based immunotherapy.

Breast cancer remains one of the leading causes of death in women around the world. A majority of deaths from breast cancer occur due to cancer cells colonizing distant organ sites. When colonizing these distant organ sites, breast cancer cells have been known to enter into a state of dormancy for extended periods of time. However, the mechanisms that promote dormancy as well as dormant-to-proliferative switch are not fully understood. The tumor microenvironment plays a key role in mediating cancer cell phenotype including regulation of the dormant state. In this review, we highlight cell-cell interactions in the tumor microenvironment mediating breast cancer dormancy at the primary and metastatic sites. Specifically, we describe how immune cells from the lymphoid lineage, tumor-associated myeloid lineage cells, and stromal cells of non-hematopoietic origin as well as tissue resident stromal cells impact dormancy vs. proliferation in breast cancer cells as well as the associated mechanisms. In addition, we highlight the importance of developing model systems and the associated considerations that will be critical in unraveling the mechanisms that promote primary and metastatic breast cancer dormancy mediated via cell-cell interactions.

Existing algorithms for assessing tumor purity are limited to a single omics data, such as gene expression, somatic copy number variations, somatic mutations, and DNA methylation. Here we proposed the machine learning Multi-omics Tumor Purity prediction (MoTP) algorithm to estimate tumor purity based on multiple types of omics data. MoTP utilizes the Bayesian Regularized Neural Networks as the prediction algorithm, and Consensus Tumor Purity Estimates as labels. We trained MoTP using multi-omics data (mRNA, microRNA, long non-coding RNA, and DNA methylation) across 21 TCGA solid cancer types. By testing MoTP in TCGA validation sets, TCGA test sets, and eight datasets outside the TCGA cancer cohorts, we showed that although MoTP could achieve excellent performance in predicting tumor purity based on a single omics data type, the integration of multiple single omics data-based predictions can enhance the prediction performance. Moreover, we demonstrated the robustness of MoTP by testing it in datasets with Gaussian noise and feature missing. Benchmark analysis showed that MoTP outperformed most established tumor purity prediction algorithms, and that it required less running time and computational resource to fulfill the predictive task. Thus, MoTP would be an attractive option for computational tumor purity inference.

NOTCH1 signaling, a vital regulator of cell proliferation and differentiation, is widely involved in the occurrence and development of malignant tumors. Pharmacological regulation of NOTCH1 is promising in tumor immunotherapy, whereas the effective rate of existing therapies remains low. NOTCH1 functions, as a cancer suppressor or a cancer promoter in different cancers, is engaged in the crosstalk between the immune microenvironment and cancer cells, posing a major challenge to immunotherapy. Therefore, a comprehensive view of the overall situation of NOTCH1-associated immune infiltration in pan-cancer should be built. The relation between NOTCH1 and immune infiltration was initially investigated in this paper. In this study, the data originated from the Genotype-Tissue Expression (GTEx) and the Cancer Genome Atlas (TCGA) databases were input into multiple online bioinformatic tools to study the characteristics of NOTCH1 in pan-cancer. We found that there was obvious heterogeneity in the NOTCH1-associated tumor immune infiltration in pan-cancer. In accordance with the heterogeneity, pan-cancer mainly fell into two categories, i.e., cancers that NOTCH1 promoted immune infiltration (termed hot tumors) and NOTCH1 inhibited immune infiltration (termed cold tumors). We further analyzed the changes of immune infiltration in pan-carcinoma species from the perspectives of NOTCH1 expression, mutation, gene function, tumor metastasis and drugs. NOTCH1 expression was significantly up-regulated in cold tumors but down-regulated in hot tumors. The Gene ontology (GO) enrichment analysis of NOTCH1 with the two categories placed stress on angiogenesis and protein dealkylation, respectively. Further, the gene sets of angiogenesis facilitated immune infiltration, whereas the gene sets of protein dealkylation hindered immune infiltration. The tsRNA associated with NOTCH1 is a type of angiogenin that potentially exerts a significant influence on angiogenesis. We have conducted a meticulous analysis of the function of this tsRNA. NOTCH1 was conducive to cancer-associated fibroblasts (CAFs) immune infiltration, while the metastatic process was more dependent on the differentiation and angiogenesis function of NOTCH1. Accordingly, the heterogeneity of NOTCH1 in immune infiltration was extensively analyzed in this study based on the pan-cancer study, which can contribute to the formulation of specific immunotherapy strategies.

Although metastatic disease is the leading cause of cancer-related deaths, its tumor microenvironment remains poorly characterized due to technical and biospecimen limitations. In this study, we assembled a multi-modal spatial and cellular map of 67 tumor biopsies from 60 patients with metastatic breast cancer across diverse clinicopathological features and nine anatomic sites with detailed clinical annotations. We combined single-cell or single-nucleus RNA sequencing for all biopsies with a panel of four spatial expression assays (Slide-seq, MERFISH, ExSeq and CODEX) and H&E staining of consecutive serial sections from up to 15 of these biopsies. We leveraged the coupled measurements to provide reference points for the utility and integration of different experimental techniques and used them to assess variability in cell type composition and expression as well as emerging spatial expression characteristics across clinicopathological and methodological diversity. Finally, we assessed spatial expression and co-localization features of macrophage populations, characterized three distinct spatial phenotypes of epithelial-to-mesenchymal transition and identified expression programs associated with local T cell infiltration versus exclusion, showcasing the potential of clinically relevant discovery in such maps.

To ascertain the prognostic role of the expression levels of estrogen receptor (ER) and progesterone receptor (PR) within the stroma microenvironment of cervical cancer and explore their correlation with clinical parameters.

This retrospective cohort study involved patients with cervical cancer diagnosed and treated at Hualien Tzu Chi Hospital between 2000 and 2010. ERα, PRB, and PR (A + B) expression levels in 169 cervical carcinoma samples, including both the tumor and stromal components, were independently scored by two pathologists, and survival and clinicopathological parameters were analyzed.

ERα or PRs were predominantly expressed in the stromal compartment rather than within cervical cancer cells. Their expression was observed comprehensively within the intra- and peritumor stroma cells. A stromal PRB expression significantly correlated with a lower 5-year mortality because of cervical cancer (p = 0.011). Particularly, levels of both stromal ERα and PRB expressions correlated with lower hematogenous distant metastase rates (p = 0.013 and p = 0.011, respectively). In the multivariable logistic regression analyses, stromal PRB independently conferred a lower risk of 5-year mortality (p = 0.022), regardless of age, histology, International Federation of Gynecology and Obstetrics (FIGO) stage, tumor differentiation, lymphovascular space invasion, and lymphatic and hematogenous metastases. Moreover, the incorporation of stromal PR (A + B) and PRB expression in the FIGO stage significantly enhanced the accuracy of survival prediction.

Stromal PRB expression emerges as an independent and favorable prognostic marker for cervical squamous cell carcinoma and correlated with a low risk of hematogenous metastases. The findings imply that incorporating this marker into the FIGO stage better predicts the survival for cervical cancer.

Lactylation, a recently identified form of protein post-translational modification (PTM), has emerged as a key player in cancer biology. The Warburg effect, a hallmark of tumour metabolism, underscores the significance of lactylation in cancer progression. By regulating gene transcription and protein function, lactylation facilitates metabolic reprogramming, enabling tumours to adapt to nutrient limitations and sustain rapid growth. Over the past decade, extensive research has revealed the intricate regulatory network underlying lactylation in tumours. Large-scale sequencing and machine learning have confirmed the widespread occurrence of lactylation sites across the tumour proteome. Targeting lactylation enzymes or metabolic pathways has demonstrated promising anti-tumour effects, highlighting the therapeutic potential of this modification. This review comprehensively explores the mechanisms of lactylation in cancer cells and the tumour microenvironment. We expound on the application of advanced omics technologies for target identification and data modelling within the lactylation field. Additionally, we summarise existing anti-lactylation drugs and discuss their clinical implications. By providing a comprehensive overview of recent advancements, this review aims to stimulate innovative research and accelerate the translation of lactylation-based therapies into clinical practice. KEY POINTS: Lactylation significantly influences tumour metabolism and gene regulation, contributing to cancer progression. Advanced sequencing and machine learning reveal widespread lactylation sites in tumours. Targeting lactylation enzymes shows promise in enhancing anti-tumour drug efficacy and overcoming chemotherapy resistance. This review outlines the clinical implications and future research directions of lactylation in oncology.

To develop and validate a radiomic model for differentiating pulmonary invasive adenocarcinomas from benign lesions based on follow-up longitudinal CT images.

This is a retrospective study including 336 patients (161 with invasive adenocarcinomas and 175 with benign lesions) who underwent baseline (T0) and follow-up (T1) CT scans from January 2016 to June 2022. The patients were randomized in a 7:3 ratio into training and test sets. Radiomic features were extracted from lesion volumes of interest on longitudinal CT images at T0 and T1. Differences in radiomic features between T1 and T0 were defined as delta-radiomic features. Logistic regression was used to build models based on clinicoradiological (CR), T0, T1, and delta radiomic features and compute signatures. Finally, a nomogram based on the CR, T0, T1 and delta signatures was constructed. Model performance was evaluated for calibration, discrimination, and clinical utility.

The T1 radiomic model was superior to the other independent models. In the training set, it had an area under the curve (AUC) of 0.858), superior to the CR model (AUC 0.694), the T0 radiomic model (AUC 0.825), and the delta radiomic model (AUC 0.734). In the test set, it had an AUC of 0.817, again outperforming the CR model (AUC 0.578), the T0 radiomic model (AUC 0.789), and the delta radiomic model (AUC 0.647). The nomogram incorporating the CR, T0, T1 and delta signatures showed the best predictive performance in both the training (AUC: 0.906) and test sets (AUC: 0.856), and it exhibited excellent fit with calibration curves. Decision curve analysis provided additional validation of the clinical utility of the nomogram.

A nomogram utilizing radiomic features extracted from longitudinal CT images can enhance the discriminative capability between pulmonary invasive adenocarcinomas and benign lesions.

Our approaches toward understanding cancer have evolved beyond cell-intrinsic and local microenvironmental changes within the tumor to encompass how the cancer interfaces with the entire host organism. The nervous system is uniquely situated at the interface between the brain and body, constantly receiving and sending signals back and forth to maintain homeostasis and respond to salient stimuli. It is becoming clear that various cancers disrupt this dialog between the brain and body via both neuronal and humoral routes, leading to aberrant brain activity and accelerated disease. In this outlook, I discuss this view of cancer as a homeostatic challenge, emphasize cutting-edge work, and provide outstanding questions that need to be answered to move the field forward.

Macrophages are usually present in solid tumors where they participate in tumor progression, angiogenesis, immunosuppression and metastasis. The design of nanocarriers capable of delivering therapeutic agents to specific cell populations has received considerable attention in the last decades. However, the capacity of many of these nanosystems to deliver multiple therapeutic agents with very different chemical properties is more limited. Herein, a novel multitasking nanoplatform capable of delivering large macromolecules and cytotoxic drugs to macrophages is presented. This novel nanosystem has exhibited excellent skills in performing simultaneous tasks, macrophage depletion and glucose starvation, maintaining the oxygen levels in the tissue. This nanodevice is composed of a dual-pore mesoporous silica core with the capacity to house small cytotoxic drugs, such as doxorubicin or zoledronic acid, and large macromolecules, such as glucose oxidase. The external surface of the silica core was coated with a lipid bilayer to avoid the premature release of the housed drugs. Finally, polymeric nanocapsules loaded with catalase were covalently anchored on the outer lipid bilayer, and carboxy-mannose was attached to the exposed side of the nanocapsules to provide selectivity to the macrophages. These nanoassemblies were able to transport enzymes (Gox and CAT), maintaining their catalytic activity. Therefore, they could induce glucose starvation, keeping the oxygen levels in the tissue, owing to the tandem enzymatic reaction. The capacity of these nanoassemblies to deliver therapeutic agents to macrophages was evaluated both in static and under flow conditions, showing a rapid capture of the nanoparticles by the macrophages. Once there, the nanoassemblies also exhibited excellent capacity to induce potent macrophage depletion. This strategy can be directly adapted for the treatment of different malignancies due to the modular nature of the nanoplatform, which can be loaded with different therapeutic agent combinations and pave the way for the development of personalized nanomedicines for diverse types of tumors.