Tumor heterogeneity: causes and consequences

Advanced tumor organoid bioprinting strategy for oncology research

Bioprinting is a groundbreaking technology that enables precise distribution of cell-containing bioinks to construct organoid models that accurately reflect the characteristics of tumors in vivo. By incorporating different types of tumor cells into the bioink, the heterogeneity of tumors can be replicated, enabling studies to simulate real-life situations closely. Precise reproduction of the arrangement and interactions of tumor cells using bioprinting methods provides a more realistic representation of the tumor microenvironment. By mimicking the complexity of the tumor microenvironment, the growth patterns and diffusion of tumors can be demonstrated. This approach can also be used to evaluate the response of tumors to drugs, including drug permeability and cytotoxicity, and other characteristics. Therefore, organoid models can provide a more accurate oncology research and treatment simulation platform. This review summarizes the latest advancements in bioprinting to construct tumor organoid models. First, we describe the bioink used for tumor organoid model construction, followed by an introduction to various bioprinting methods for tumor model formation. Subsequently, we provide an overview of existing bioprinted tumor organoid models.

Evaluation of Cellpose segmentation with sequential thresholding for instance segmentation of cytoplasms within autofluorescence images

BACKGROUND

Autofluorescence imaging of the coenzyme, reduced nicotinamide adenine dinucleotide (phosphate) (NAD(P)H), provides a label-free technique to assess cellular metabolism. Because NAD(P)H is localized in the cytosol and mitochondria, instance segmentation of cell cytoplasms from NAD(P)H images allows quantification of metabolism with cellular resolution. However, accurate cytoplasmic segmentation of autofluorescence images is difficult due to irregular cell shapes and cell clusters.

METHOD

Here, a cytoplasm segmentation method is presented and tested. First, autofluorescence images are segmented into cells via either hand-segmentation or Cellpose, a deep learning-based segmentation method. Then, a cytoplasmic post-processing algorithm (CPPA) is applied for cytoplasmic segmentation. CPPA uses a binarized segmentation image to remove non-segmented pixels from the NAD(P)H image and then applies an intensity-based threshold to identify nuclei regions. Errors at cell edges are removed using a distance transform algorithm. The nucleus mask is then subtracted from the cell segmented image to yield the cytoplasm mask image. CPPA was tested on five NAD(P)H images of three different cell samples, quiescent T cells, activated T cells, and MCF7 cells.

RESULTS

Using POSEA, an evaluation method tailored for instance segmentation, the CPPA yielded F-measure values of 0.89, 0.87, and 0.94 for quiescent T cells, activated T cells, and MCF7 cells, respectively, for cytoplasm identification of hand-segmented cells. CPPA achieved F-measure values of 0.84, 0.74, and 0.72 for Cellpose segmented cells.

CONCLUSION

These results exceed the F-measure value of a comparative cell segmentation method (CellProfiler, ∼0.50-0.60) and support the use of artificial intelligence and post-processing techniques for accurate segmentation of autofluorescence images for single-cell metabolic analyses.

Insights into metabolic heterogeneity of colorectal cancer gained from fluorescence lifetime imaging

Heterogeneity of tumor metabolism is an important, but still poorly understood aspect of tumor biology. Present work is focused on the visualization and quantification of cellular metabolic heterogeneity of colorectal cancer using fluorescence lifetime imaging (FLIM) of redox cofactor NAD(P)H. FLIM-microscopy of NAD(P)H was performed in vitro in four cancer cell lines (HT29, HCT116, CaCo2 and CT26), in vivo in the four types of colorectal tumors in mice and ex vivo in patients' tumor samples. The dispersion and bimodality of the decay parameters were evaluated to quantify the intercellular metabolic heterogeneity. Our results demonstrate that patients' colorectal tumors have significantly higher heterogeneity of energy metabolism compared with cultured cells and tumor xenografts, which was displayed as a wider and frequently bimodal distribution of a contribution of a free (glycolytic) fraction of NAD(P)H within a sample. Among patients' tumors, the dispersion was larger in the high-grade and early stage ones, without, however, any association with bimodality. These results indicate that cell-level metabolic heterogeneity assessed from NAD(P)H FLIM has a potential to become a clinical prognostic factor.

Evolutionary Measures Show that Recurrence of DCIS is Distinct from Progression to Breast Cancer

Progression from pre-cancers like ductal carcinoma in situ (DCIS) to invasive disease (cancer) is driven by somatic evolution and is altered by clinical interventions. We hypothesized that genetic and/or phenotypic intra-tumor heterogeneity would predict clinical outcomes for DCIS since it serves as the substrate for natural selection among cells. We profiled two samples from two geographically distinct foci from each DCIS in both cross-sectional (N = 119) and longitudinal cohorts (N = 224), with whole exome sequencing, low-pass whole genome sequencing, and a panel of immunohistochemical markers. In the longitudinal cohorts, the only statistically significant predictors of time to non-invasive DCIS recurrence were the combination of treatment (lumpectomy only vs mastectomy or lumpectomy with radiation, HR = 12.13, p = 0.003, Wald test with FDR correction), ER status (HR = 0.16 for ER+ compared to ER-, p = 0.0045), and divergence in SNVs between the two samples (HR = 1.33 per 10% divergence, p = 0.018). SNV divergence also distinguished between pure DCIS and DCIS synchronous with invasive disease in the cross-sectional cohort. In contrast, the only statistically significant predictors of time to progression to invasive disease were the combination of the width of the surgical margin (HR = 0.67 per mm, p = 0.043) and the number of mutations that were detectable at high allele frequencies (HR = 1.30 per 10 SNVs, p = 0.02). These results imply that recurrence with DCIS is a clinical and biological process different from invasive progression.

Significance

Evolutionary measures of breast pre-cancers associate with local recurrence after surgery, as well as progression to cancer. Recurrence and progression are different biological processes impacted differently by clinical interventions.

Antibody Drug Conjugates for Cancer Therapy: From Metallodrugs to Nature-Inspired Payloads

This review highlights significant advancements in antibody-drug conjugates (ADCs) equipped with metal-based and nature-inspired payloads, focusing on synthetic strategies for antibody conjugation. Traditional methods such us maleimide and succinimide conjugation and classical condensation reactions are prevalent for metallodrugs and natural compounds. However, emerging non-conventional strategies such as photoconjugation are gaining traction due to their milder conditions and, in an aspect which minimizes side reactions, selective formation of ADC. The review also summarizes the therapeutic and diagnostic properties of these ADCs, highlighting their enhanced selectivity and reduced side effects in cancer treatment compared to non-conjugated payloads. ADCs combine the specificity of monoclonal antibodies with the cytotoxicity of chemotherapy drugs, offering a targeted approach to the elimination of cancer cells while sparing healthy tissues. This targeted mechanism has demonstrated impressive clinical efficacy in various malignancies. Key future advancements include improved linker technology for enhanced stability and controlled release of cytotoxic agents, incorporation of novel, more potent, cytotoxic agents, and the identification of new cancer-specific antigens through genomic and proteomic technologies. ADCs are also expected to play a crucial role in combination therapies with immune checkpoint inhibitors, CAR-T cells, and small molecule inhibitors, leading to more durable and potentially curative outcomes. Ongoing research and clinical trials are expanding their capabilities, paving the way for more effective, safer, and personalized treatments, positioning ADCs as a cornerstone of modern medicine and offering new hope to patients.

Capturing cell heterogeneity in representations of cell populations for image-based profiling using contrastive learning

Image-based cell profiling is a powerful tool that compares perturbed cell populations by measuring thousands of single-cell features and summarizing them into profiles. Typically a sample is represented by averaging across cells, but this fails to capture the heterogeneity within cell populations. We introduce CytoSummaryNet: a Deep Sets-based approach that improves mechanism of action prediction by 30-68% in mean average precision compared to average profiling on a public dataset. CytoSummaryNet uses self-supervised contrastive learning in a multiple-instance learning framework, providing an easier-to-apply method for aggregating single-cell feature data than previously published strategies. Interpretability analysis suggests that the model achieves this improvement by downweighting small mitotic cells or those with debris and prioritizing large uncrowded cells. The approach requires only perturbation labels for training, which are readily available in all cell profiling datasets. CytoSummaryNet offers a straightforward post-processing step for single-cell profiles that can significantly boost retrieval performance on image-based profiling datasets.

Clinicopathological significance of mutation profile detected by next generation sequencing in different metastatic organs of non-small cell lung cancers

BACKGROUND

The primary tumor and it's metastases show heterogeneity in molecular studies for targeted therapies in Non-Small Cell Lung Cancer(NSCLC), the leading cause of cancer-related deaths worldwide. The study aimed to identify somatic mutations in biopsies from NSCLC patients' metastatic organs using Next-Generation Sequencing(NGS) and examine their association with clinicopathological parameters.

MATERIALS AND METHODS

The study included 128 NSCLC patients and, NGS was performed on tumor biopsies from different metastatic organs at Molecular Pathology laboratory of the Department of Medical Pathology in Aydın Adnan Menderes University Faculty of Medicine. The age, gender, histopathological diagnoses, metastatic organs, smoking and mutation status were all recorded, along with the analysis results of 72 genes and 4149 primers in the panel of the NGS system.

RESULTS

53.9 % of the cases had a history of smoking and patients with brain metastases had a higher smoking rate(p=0.000). The most common occurrence(39.8 %) was lymph node metastasis, followed by brain(19.5 %). There was a strong correlation between mutation presence and metastasis in the liver(p=0.012), bone(p=0.002), and pleura(p=0.008). Smokers had a higher frequency of KRAS(p=0.000) and TP53(p=0.001) mutations. Brain metastases showed a statistically significant NF1 mutation(p=0.001), while the liver exhibited a significant BRAF mutation(p=0.000). NF1-TP53, PTEN-TP53 and NF1-PTEN were the most common concomitant mutations and, the brain was the most common metastatic organ in which they occurred.

CONCLUSION

Our results suggest prizing assessing detected mutations, in the prediction, follow-up and management of metastases, especially in patients with lung adenocarcinoma. The assessment also needs to consider the tumor's mutation status in metastatic organs. New therapeutic agents targeting NF1 mutations will be available in the future to treat NSCLC, especially in metastases.

S-allyl-cysteine triggers cytotoxic events in rat glioblastoma RG2 and C6 cells and improves the effect of temozolomide through the regulation of oxidative responses

Glioblastoma (GBM) is an aggressive form of cancer affecting the Central Nervous System (CNS) of thousands of people every year. Redox alterations have been shown to play a key role in the development and progression of these tumors as Reactive Oxygen Species (ROS) formation is involved in the modulation of several signaling pathways, transcription factors, and cytokine formation. The second-generation oral alkylating agent temozolomide (TMZ) is the first-line chemotherapeutic drug used to treat of GBM, though patients often develop primary and secondary resistance, reducing its efficacy. Antioxidants represent promising and potential coadjutant agents as they can reduce excessive ROS formation derived from chemo- and radiotherapy, while decreasing pharmacological resistance. S-allyl-cysteine (SAC) has been shown to inhibit the proliferation of several types of cancer cells, though its precise antiproliferative mechanisms remain poorly investigated. To date, SAC effects have been poorly explored in GBM cells. Here, we investigated the effects of SAC in vitro, either alone or in combination with TMZ, on several toxic and modulatory endpoints-including oxidative stress markers and transcriptional regulation-in two glioblastoma cell lines from rats, RG2 and C6, to elucidate some of the biochemical and cellular mechanisms underlying its antiproliferative properties. SAC (1-750 µM) decreased cell viability in both cell lines in a concentration-dependent manner, although C6 cells were more resistant to SAC at several of the tested concentrations. TMZ also produced a concentration-dependent effect, decreasing cell viability of both cell lines. In combination, SAC (1 µM or 100 µM) and TMZ (500 µM) enhanced the effects of each other. SAC also augmented the lipoperoxidative effect of TMZ and reduced cell antioxidant resistance in both cell lines by decreasing the TMZ-induced increase in the GSH/GSSG ratio. In RG2 and C6 cells, SAC per se had no effect on Nrf2/ARE binding activity, while in RG2 cells TMZ and the combination of SAC + TMZ decreased this activity. Our results demonstrate that SAC, alone or in combination with TMZ, exerts antitumor effects mediated by regulatory mechanisms of redox activity responses. SAC is also a safe drug for testing in other models as it produces non-toxic effects in primary astrocytes. Combined, these effects suggest that SAC affords antioxidant properties and potential antitumor efficacy against GBM.

Organoid Cultures for the Study of Mammary Biology and Breast Cancer: The Promise and Challenges

During the last decade, biomedical research has experienced a resurgence in the use of three-dimensional culture models for studies of normal and cancer biology. This resurgence has been driven by the development of models in which primary cells are grown in tissue-mimicking media and extracellular matrices to create organoid or organotypic cultures that more faithfully replicate the complex architecture and physiology of normal tissues and tumors. In addition, patient-derived tumor organoids preserve the three-dimensional organization and characteristics of the patient tumors ex vivo, becoming excellent preclinical models to supplement studies of tumor xenografts transplanted into immunocompromised mice. In this perspective, we provide an overview of how organoids are being used to investigate normal mammary biology and as preclinical models of breast cancer and discuss improvements that would enhance their utility and relevance to the field.

A modelling framework for cancer ecology and evolution

Cancer incidence increases rapidly with age, typically as a polynomial. The somatic mutation theory explains this increase through the waiting time for enough mutations to build up to generate cells with the full set of traits needed to grow without control. However, lines of evidence ranging from tumour reversion and dormancy to the prevalence of presumed cancer mutations in non-cancerous tissues argue that this is not the whole story, and that cancer is also an ecological process, and that mutations only lead to cancer when the systems of control within and across cells have broken down. Aging thus has two effects: the build-up of mutations and the breakdown of control. This paper presents a mathematical modelling framework to unify these theories with novel approaches to model the mutation and diversification of cell lineages and of the breakdown of the layers of control both within and between cells. These models correctly predict the polynomial increase of cancer with age, show how germline defects in control accelerate cancer initiation, and compute how the positive feedback between cell replication, ecology and layers of control leads to a doubly exponential growth of cell populations.

Mechanism of the Radioresistant Colorectal Cancer Cell Line SW480RR Established after Fractionated X Irradiation

Radioresistant cancer cells are risk factors for recurrence and are occasionally detected in recurrent tumors after radiotherapy. Intratumor heterogeneity is believed to be a potential cause of treatment resistance. Heterogeneity in DNA content has also been reported in human colorectal cancer; however, little is known about how such heterogeneity changes with radiotherapy or how it affects cancer radioresistance. In the present study, we established radioresistant clone SW480RR cells after fractionated X-ray irradiation of human colorectal cancer-derived SW480.hu cells, which are composed of two cell populations with different chromosome numbers, and examined how cellular radioresistance changed with fractionated radiotherapy. Compared with the parental cell population, which mostly comprised cells with higher ploidy, the radioresistant clones showed lower ploidy and less initial DNA damage. The lower ploidy cells in the parental cell population were identified as having radioresistance prior to irradiation; thus, SW480RR cells were considered intrinsically radioresistant cells selected from the parental population through fractionated irradiation. This study presents a practical example of the emergence of radioresistant cells from a cell population with ploidy heterogeneity after irradiation. The most likely mechanism is the selection of an intrinsically radioresistant population after fractionated X-ray irradiation, with a background in which lower ploidy cells exhibit lower initial DNA damage.

Engineering principles for rationally design therapeutic strategies against hepatocellular carcinoma

The search for new therapeutic strategies against cancer has favored the emergence of rationally designed treatments. These treatments have focused on attacking cell plasticity mechanisms to block the transformation of epithelial cells into cancerous cells. The aim of these approaches was to control particularly lethal cancers such as hepatocellular carcinoma. However, they have not been able to control the progression of cancer for unknown reasons. Facing this scenario, emerging areas such as systems biology propose using engineering principles to design and optimize cancer treatments. Beyond the possibilities that this approach might offer, it is necessary to know whether its implementation at a clinical level is viable or not. Therefore, in this paper, we will review the engineering principles that could be applied to rationally design strategies against hepatocellular carcinoma, and discuss whether the necessary elements exist to implement them. In particular, we will emphasize whether these engineering principles could be applied to fight hepatocellular carcinoma.

In silico study of heterogeneous tumour-derived organoid response to CAR T-cell therapy

Chimeric antigen receptor (CAR) T-cell therapy is a promising immunotherapy for treating cancers. This method consists in modifying the patients' T-cells to directly target antigen-presenting cancer cells. One of the barriers to the development of this type of therapies, is target antigen heterogeneity. It is thought that intratumour heterogeneity is one of the leading determinants of therapeutic resistance and treatment failure. While understanding antigen heterogeneity is important for effective therapeutics, a good therapy strategy could enhance the therapy efficiency. In this work we introduce an agent-based model (ABM), built upon a previous ABM, to rationalise the outcomes of different CAR T-cells therapies strategies over heterogeneous tumour-derived organoids. We found that one dose of CAR T-cell therapy should be expected to reduce the tumour size as well as its growth rate, however it may not be enough to completely eliminate it. Moreover, the amount of free CAR T-cells (i.e. CAR T-cells that did not kill any cancer cell) increases as we increase the dosage, and so does the risk of side effects. We tested different strategies to enhance smaller dosages, such as enhancing the CAR T-cells long-term persistence and multiple dosing. For both approaches an appropriate dosimetry strategy is necessary to produce "effective yet safe" therapeutic results. Moreover, an interesting emergent phenomenon results from the simulations, namely the formation of a shield-like structure of cells with low antigen expression. This shield turns out to protect cells with high antigen expression. Finally we tested a multi-antigen recognition therapy to overcome antigen escape and heterogeneity. Our studies suggest that larger dosages can completely eliminate the organoid, however the multi-antigen recognition increases the risk of side effects. Therefore, an appropriate small dosages dosimetry strategy is necessary to improve the outcomes. Based on our results, it is clear that a proper therapeutic strategy could enhance the therapies outcomes. In that direction, our computational approach provides a framework to model treatment combinations in different scenarios and to explore the characteristics of successful and unsuccessful treatments.

In Situ Detection of Nucleic Acids in Extracellular Vesicles via Membrane Fusion

Extracellular vesicles (EVs) carry diverse biomolecules (e. g., nucleic acids, proteins) for intercellular communication, serving as important markers for diseases. Analyzing nucleic acids derived from EVs enables non-invasive disease diagnosis and prognosis evaluation. Membrane fusion, a fundamental cellular process wherein two lipid membranes merge, facilitates cell communication and cargo transport. Building on this natural phenomenon, recent years have witnessed the emergence of membrane fusion-based strategies for the detection of nucleic acids within EVs. These strategies entail the encapsulation of detection probes within either artificial or natural vesicles, followed by the induction of membrane fusion with EVs to deliver probes. This innovative approach not only enables in situ detection of nucleic acids within EVs but also ensures the maintenance of structural integrity of EVs, thus preventing nucleic acid degradation and minimizing the interference from free nucleic acids. This concept categorizes approaches into universal and targeted membrane fusion strategies, and discusses their application potential, and challenges and future prospects.

Advancement in Cancer Vasculogenesis Modeling through 3D Bioprinting Technology

Cancer vasculogenesis is a pivotal focus of cancer research and treatment given its critical role in tumor development, metastasis, and the formation of vasculogenic microenvironments. Traditional approaches to investigating cancer vasculogenesis face significant challenges in accurately modeling intricate microenvironments. Recent advancements in three-dimensional (3D) bioprinting technology present promising solutions to these challenges. This review provides an overview of cancer vasculogenesis and underscores the importance of precise modeling. It juxtaposes traditional techniques with 3D bioprinting technologies, elucidating the advantages of the latter in developing cancer vasculogenesis models. Furthermore, it explores applications in pathological investigations, preclinical medication screening for personalized treatment and cancer diagnostics, and envisages future prospects for 3D bioprinted cancer vasculogenesis models. Despite notable advancements, current 3D bioprinting techniques for cancer vasculogenesis modeling have several limitations. Nonetheless, by overcoming these challenges and with technological advances, 3D bioprinting exhibits immense potential for revolutionizing the understanding of cancer vasculogenesis and augmenting treatment modalities.

Modeling tumors as species-rich ecological communities

Many advanced cancers resist therapeutic intervention. This process is fundamentally related to intra-tumor heterogeneity: multiple cell populations, each with different mutational and phenotypic signatures, coexist within a tumor and its metastatic nodes. Like species in an ecosystem, many cancer cell populations are intertwined in a complex network of ecological interactions. Most mathematical models of tumor ecology, however, cannot account for such phenotypic diversity nor are able to predict its consequences. Here we propose that the Generalized Lotka-Volterra model (GLV), a standard tool to describe complex, species-rich ecological communities, provides a suitable framework to describe the ecology of heterogeneous tumors. We develop a GLV model of tumor growth and discuss how its emerging properties, such as outgrowth and multistability, provide a new understanding of the disease. Additionally, we discuss potential extensions of the model and their application to three active areas of cancer research, namely phenotypic plasticity, the cancer-immune interplay and the resistance of metastatic tumors to treatment. Our work outlines a set of questions and a tentative road map for further research in cancer ecology.

Extrachromosomal circular DNA (eccDNA): from carcinogenesis to drug resistance

Extrachromosomal circular DNA (eccDNA) is a circular form of DNA that exists outside of the chromosome. Although it has only been a few decades since its discovery, in recent years, it has been found to have a close relationship with cancer, which has attracted widespread attention from researchers. Thus far, under the persistent research of researchers from all over the world, eccDNA has been found to play an important role in a variety of tumors, including breast cancer, lung cancer, ovarian cancer, etc. Herein, we review the sources of eccDNA, classifications, and the mechanisms responsible for their biogenesis. In addition, we introduce the relationship between eccDNA and various cancers and the role of eccDNA in the generation and evolution of cancer. Finally, we summarize the research significance and importance of eccDNA in cancer, and highlight new prospects for the application of eccDNA in the future detection and treatment of cancer.

Identifying Optimal Candidates for Primary Tumor Resection Among Metastatic Pancreatic Cancer Patients: A Population-Based Predictive Model

BACKGROUND

There is a controversy about whether surgery should proceed among metastatic pancreatic cancer (mPC) patients. A survival benefit was observed in mPC patients who underwent primary tumor resection; however, determining which patients would benefit from surgery is complex. For this purpose, we created a model to identify mPC patients who may benefit from primary tumor excision.

METHODS

Patients with mPC were extracted from the Surveillance, Epidemiology, and End Results database, and separated into surgery and nonsurgery groups based on whether the primary tumor was resected. Propensity score matching (PSM) was applied to balance confounding factors between the two groups. A nomogram was developed using multivariable logistic regression to estimate surgical benefit. Our model is evaluated using multiple methods.

RESULTS

About 662 of 14,183 mPC patients had primary tumor surgery. Kaplan-Meier analyses showed that the surgery group had a better prognosis. After PSM, a survival benefit was still observed in the surgery group. Among the surgery cohort, 202 patients survived longer than 4 months (surgery-beneficial group). The nomogram discriminated better in training and validation sets under the receiver operating characteristic (ROC) curve (AUC), and calibration curves were consistent. Decision curve analysis (DCA) revealed that it was clinically valuable. This model is better at identifying candidates for primary tumor excision.

CONCLUSION

A helpful prediction model was developed and validated to identify ideal candidates who may benefit from primary tumor resection in mPC.

Tumor Microenvironment-Induced Drug Depository for Persistent Antitumor Chemotherapy and Immune Activation

Herein, a drug-loading nanosystem that can in situ form drug depository for persistent antitumor chemotherapy and immune regulation is designed and built. The system (DOX@MIL-LOX@AL) is fabricated by packaging alginate on the surface of Doxorubicin (DOX) and lactate oxidase (LOX) loaded MIL-101(Fe)-NH2 nanoparticle, which can easily aggregate in the tumor microenvironment through the cross-linking with intratumoral Ca2+. Benefiting from the tumor retention ability, the fast-formed drug depository will continuously release DOX and Fe ions through the ATP-triggered slow degradation, thus realizing persistent antitumor chemotherapy and immune regulation. Meanwhile, LOX in the non-aggregated nanoparticles is able to convert the lactic acid to H2O2, which will be subsequently decomposed into ·OH by Fe ions to further enhance the DOX-induced immunogenic death effect of tumor cells. Together, with the effective consumption of immunosuppressive lactic acid, long-term chemotherapy, and oxidation therapy, DOX@MIL-LOX@AL can execute high-performance antitumor chemotherapy and immune activation with only one subcutaneous administration.

Exploring neutrophil functionality in breast cancer progression: A review

Breast cancer remains a pressing global health concern, with a myriad of intricate factors contributing to its development, progression, and heterogeneity. Among these multifaceted elements, the role of immune cells within the tumor microenvironment is gaining increasing attention. In this context, neutrophils, traditionally regarded as the first responders to infections, are emerging as noteworthy participants in the complex landscape of breast cancer. This paper seeks to unravel the intricate and multifaceted role of neutrophils in breast cancer. Neutrophils, classically known for their phagocytic and pro-inflammatory functions, are now recognized for their involvement in promoting or restraining tumor growth. While their presence within the tumor microenvironment may exert antitumor effects through immune surveillance and cytotoxic activities, these innate immune cells can also facilitate tumor progression by fostering an immunosuppressive milieu, promoting angiogenesis, and aiding metastatic dissemination. The intricacies of neutrophil-tumor cell interactions, signaling pathways, and mechanisms governing their recruitment to the tumor site are explored in detail. Challenges and gaps in current knowledge are acknowledged, and future directions for research are outlined. This review underscores the dynamic and context-dependent role of neutrophils in breast cancer and emphasizes the significance of unraveling their multifaceted contributions. As we delve into the complexities of the immune landscape in breast cancer, a deeper understanding of the warriors within, the neutrophils, presents exciting prospects for the development of novel therapeutic strategies and a more comprehensive approach to breast cancer management.

Synthesis and preclinical evaluation of BOLD-100 radiolabeled with ruthenium-97 and ruthenium-103

BOLD-100 (formerly IT-139, KP1339), a well-established chemotherapeutic agent, is currently being investigated in clinical trials for the treatment of gastric, pancreatic, colorectal, and bile duct cancer. Despite numerous studies, the exact mode of action is still the subject of discussions. Radiolabeled BOLD-100 could be a powerful tool to clarify pharmacokinetic pathways of the compound and to predict therapy responses in patients using nuclear molecular imaging prior to the therapy. In this study, the radiosyntheses of carrier-added (c.a.) [97/103Ru]BOLD-100 were performed with the two ruthenium isotopes ruthenium-103 (103Ru; β-, γ) and ruthenium-97 (97Ru; EC, γ), of which in particular the latter isotope is suitable for imaging by single-photon emission computed tomography (SPECT). To identify the best tumor-to-background ratio for diagnostic imaging, biodistribution studies were performed with two different injected doses of c.a. [103Ru]BOLD-100 (3 and 30 mg kg-1) in Balb/c mice bearing CT26 allografts over a time period of 72 h. Additionally, ex vivo autoradiography of the tumors (24 h p.i.) was conducted. Our results indicate that the higher injected dose (30 mg kg-1) leads to more unspecific accumulation of the compound in non-targeted tissue, which is likely due to an overload of the albumin transport system. It was also shown that lower amounts of injected c.a. [103Ru]BOLD-100 resulted in a relatively higher tumor uptake and, therefore, a better tumor-to-background ratio, which are encouraging results for future imaging studies using c.a. [97Ru]BOLD-100.

Neighboring macrophage-induced alteration in the phenotype of colorectal cancer cells in the tumor budding area

BACKGROUND

A higher number of tumor buds in the invasive front of colorectal cancer (CRC) specimens has been shown to contribute to a poor prognosis in CRC patients. Because macrophages (Mφs) have been demonstrated to alter the phenotype of cancer cells, we hypothesized that the phenotype of CRC cells in the tumor budding (TB) area might be changed by the interaction between CRC cells and Mφs.

METHODS

We assessed the expression of topoisomerase 1 in CRC cells to estimate the acquisition of chemoresistance in CRC. To demonstrate the tumor-stromal interaction between CRC cells and Mφs, we assessed two histological findings, the number of Mφs per single CRC cell and the proximity between CRC cells and Mφs by histological spatial analysis using HALO software.

RESULTS

The expression levels of topoisomerase 1 in CRC cells were decreased in deeper areas, especially in the TB area, compared to the surface area. Our histological spatial analysis revealed that 2.6 Mφs located within 60 μm of a single CRC cell were required to alter the phenotype of the CRC cell. Double-immunofluorescence staining revealed that higher Mφs were positive for interleukin-6 (IL-6) in the TB area and that AE1/AE3-positive CRC cells were also positive for phospho-STAT3 (pSTAT3) in the TB area; thus, the IL-6 receptor (IL-6R)/STAT3 signaling pathway in CRC cells was upregulated by IL-6 derived from neighboring Mφs.

CONCLUSION

IL-6 secreted from the neighboring Mφs would alter the phenotype of CRC cells via IL-6R/STAT3 signaling pathway.

High HER2 Intratumoral Heterogeneity Is a Predictive Factor for Poor Prognosis in Early-Stage and Locally Advanced HER2-Positive Breast Cancer

PURPOSE

Breast cancer tumors frequently have intratumoral heterogeneity (ITH). Tumors with high ITH cause therapeutic resistance and have human epidermal growth factor receptor 2 (HER2) heterogeneity in response to HER2-targeted therapies. This study aimed to investigate whether high HER2 heterogeneity levels were clinically related to a poor prognosis for HER2-targeted adjuvant therapy resistance in primary breast cancers.

METHODS

This study included patients with primary breast cancer (n = 251) treated with adjuvant HER2-targeted therapies. HER2 heterogeneity was manifested by the shape of HER2 fluorescence in situ hybridization amplification (FISH) distributed histograms with the HER2 gene copy number within a tumor sample. Each tumor was classified into a biphasic grade graph (high heterogeneity [HH]) group or a monophasic grade graph (low heterogeneity [LH]) group based on heterogeneity. Both groups were evaluated for disease-free survival (DFS) and overall survival (OS) for a median of ten years of annual follow-up.

RESULTS

Of 251 patients with HER2-positive breast cancer, 46 (18.3%) and 205 (81.7%) were classified into the HH and LH groups, respectively. The HH group had more distant metastases and a poorer prognosis than the LH group (DFS: p < 0.001 (HH:63% vs. LH:91% at 10 years) and for the OS: p = 0.012 (HH:78% vs. LH:95% at 10 years).

CONCLUSIONS

High HER2 heterogeneity is a poor prognostic factor in patients with HER2-positive breast cancer. A novel approach to heterogeneity, which is manifested by the shape of HER2 FISH distributions, might be clinically useful in the prognosis prediction of patients after HER2 adjuvant therapy.

Clinical impact of pleural fluid carcinoembryonic antigen on therapeutic strategy and efficacy in lung adenocarcinoma patients with malignant pleural effusion

BACKGROUND/AIMS

Epidermal growth factor receptor (EGFR) mutation is important in determining the treatment strategy for advanced lung cancer patients with malignant pleural effusion (MPE). Contrary to serum carcinoembryonic antigen (S-CEA) levels, the associations between pleural fluid CEA (PF-CEA) levels and EGFR mutation status as well as between PF-CEA levels and treatment efficacy have rarely been investigated in lung adenocarcinoma patients with MPE.

METHODS

This retrospective study enrolled lung adenocarcinoma patients with MPE and available PF-CEA levels and EGFR mutation results. The patients were categorized based on PF-CEA levels: < 10 ng/mL, 10-100 ng/mL, 100-500 ng/mL, and ≥ 500 ng/mL. The association between PF-CEA levels and EGFR mutation status as well as their therapeutic impact on overall survival was compared among the four groups.

RESULTS

This study included 188 patients. PF-CEA level was found to be an independent predictor of EGFR mutation but not S-CEA level. The EGFR mutation rates were higher as the PF-CEA levels increased, regardless of cytology results or sample types. Among EGFR-mutant lung adenocarcinoma patients receiving EGFR-tyrosine kinase inhibitor (TKI) treatment, those with high PF-CEA levels had significantly better survival outcomes than those with low PF-CEA levels.

CONCLUSION

High PF-CEA levels were associated with high EGFR mutation rate and may lead to a favorable clinical outcome of EGFR-TKI treatment in EGFR-mutant lung adenocarcinoma patients with MPE. These findings highlight the importance of actively investigating EGFR mutation detection in patients with suspected MPE and elevated PF-CEA levels despite negative cytology results.

Non-specific irreversible 89Zr-mAb uptake in tumours: evidence from biopsy-proven target-negative tumours using 89Zr-immuno-PET

BACKGROUND

Distribution of mAbs into tumour tissue may occur via different processes contributing differently to the 89Zr-mAb uptake on PET. Target-specific binding in tumours is of main interest; however, non-specific irreversible uptake may also be present, which influences quantification. The aim was to investigate the presence of non-specific irreversible uptake in tumour tissue using Patlak linearization on 89Zr-immuno-PET data of biopsy-proven target-negative tumours. Data of two studies, including target status obtained from biopsies, were retrospectively analysed, and Patlak linearization provided the net rate of irreversible uptake (Ki).

RESULTS

Two tumours were classified as CD20-negative and two as CD20-positive. Four tumours were classified as CEA-negative and nine as CEA-positive. Ki values of CD20-negative (0.43 µL/g/h and 0.92 µL/g/h) and CEA-negative tumours (mdn = 1.97 µL/g/h, interquartile range (IQR) = 1.50-2.39) were higher than zero. Median Ki values of target-negative tumours were lower than CD20-positive (1.87 µL/g/h and 1.90 µL/g/h) and CEA-positive tumours (mdn = 2.77 µL/g/h, IQR = 2.11-3.65).

CONCLUSION

Biopsy-proven target-negative tumours showed irreversible uptake of 89Zr-mAbs measured in vivo using 89Zr-immuno-PET data, which suggests the presence of non-specific irreversible uptake in tumours. Consequently, for 89Zr-immuno-PET, even if the target is absent, a tumour-to-plasma ratio always increases over time.

Clinical benefit, development, innovation, trials, epidemiology, and price for cancer drugs and indications with multiple special FDA designations

BACKGROUND

This study analyzes the development, US Food and Drug Administration (FDA) approval, benefits, innovation, trials, epidemiology, and price of cancer drugs with multiple special designations: orphan, fast track, accelerated approval, priority review, and breakthrough therapy.

METHODS

In total, 355 FDA-approved cancer drug indications with 841 special designations were identified (2012-2022). Trial, epidemiology, and price data were collected from FDA labels, the Global Burden of Disease study, and Medicare and Medicaid. The association between efficacy outcomes and indications' number of special designations were compared in meta-analyses.

RESULTS

Median development times were 7.3, 7.8, and 5.4 months (P = .027) for drugs with 0 to 1, 2 to 3, and 4 to 5 special designations, respectively. Multiple special designations were associated with higher biotechnological and clinical innovation. Median patient enrollment in trials were 615, 471, 398, 168, 104, and 120 (P < .001) for indications with 0 to 5 special designations. Drugs for rare diseases supported by open-label phase 1/2 trials of single-arm design were granted more special designations. Hazard ratios for overall survival (0.80 vs 0.73 vs 0.73 vs 0.69 vs 0.56 vs 0.52; P = .003) and progression-free survival (0.70 vs 0.61 vs 0.59 vs 0.44 vs 0.37 vs 0.67; P < .001) substantially declined while tumor response increased with more special designations. Mean monthly prices increased for drugs with 0 to 4 but not 5 special designations ($21 596 vs $14 753 vs $32 410 vs $41 240 vs $38 703 vs $19 184).

CONCLUSIONS

Multiple special designations are associated with faster clinical development and greater benefits for patients with unmet needs but also with nonrobust trial evidence and a tendency toward higher drug prices.

Relatively Rare Populations of Invasive Cells Drive Progression of Heterogeneous Tumors

Introduction

Breast tumors often display an astonishing degree of spatial and temporal heterogeneity, which are associated with cancer progression, drug resistance, and relapse. Triple-negative breast cancer (TNBC) is a particularly aggressive and heterogeneous subtype for which targeted therapies are scarce. Consequently, patients with TNBC have a poorer overall prognosis compared to other breast cancer patients. Within heterogeneous tumors, individual clonal subpopulations may exhibit differences in their rates of growth and degrees of invasiveness. We hypothesized that such phenotypic heterogeneity at the single-cell level may accelerate tumor progression by enhancing the overall growth and invasion of the entire tumor.

Methods

To test this hypothesis, we isolated and characterized clonal subpopulations with distinct morphologies and biomarker expression from the inherently heterogeneous 4T1 mouse mammary carcinoma cell line. We then leveraged a 3D microfluidic tumor model to reverse-engineer intratumoral heterogeneity and thus investigate how interactions between phenotypically distinct subpopulations affect tumor growth and invasion.

Results

We found that the growth and invasion of multiclonal tumors were largely dictated by the presence of cells with epithelial and mesenchymal traits, respectively. The latter accelerated overall tumor invasion, even when these cells comprised less than 1% of the initial population. Consistently, tumor progression was delayed by selectively targeting the mesenchymal subpopulation.

Discussion

This work reveals that highly invasive cells can dominate tumor phenotype and that specifically targeting these cells can slow the progression of heterogeneous tumors, which may help inform therapeutic approaches.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12195-023-00792-w.

A comprehensive review of 3D cancer models for drug screening and translational research

The 3D cancer models fill the discovery gap of 2D cancer models and play an important role in cancer research. In addition to cancer cells, a range of other factors include the stroma, density and composition of extracellular matrix, cancer-associated immune cells (e.g., cancer-associated fibroblasts cancer cell-stroma interactions and subsequent interactions, and a number of other factors (e.g., tumor vasculature and tumor-like microenvironment in vivo) has been widely ignored in the 2D concept of culture. Despite this knowledge, the continued use of monolayer cell culture methods has led to the failure of a series of clinical trials. This review discusses the immense importance of tumor microenvironment (TME) recapitulation in cancer research, prioritizing the individual roles of TME elements in cancer histopathology. The TME provided by the 3D model fulfills the requirements of in vivo spatiotemporal arrangement, components, and is helpful in analyzing various different aspects of drug sensitivity in preclinical and clinical trials, some of which are discussed here. Furthermore, it discusses models for the co-assembly of different TME elements in vitro and focuses on their synergistic function and responsiveness as tumors. Furthermore, this review broadly describes of a handful of recently developed 3D models whose main focus is limited to drug development and their screening and/or the impact of this approach in preclinical and translational research.

Unrevealing the therapeutic benefits of radiotherapy and consolidation immunotherapy using ctDNA-defined tumor clonality in unresectable locally advanced non-small cell lung cancer

Progression occurs in approximately two-thirds of patients with locally advanced non-small cell lung cancer (LA-NSCLC) receiving chemoradiation and consolidation immunotherapy. Molecular indicators for outcome prediction are under development. A novel metric, the ratio of mean to max variant allele frequency (mmVAF), was derived from 431 pre-treatment tissue biopsies from The Cancer Genome Atlas and evaluated in serial circulating tumor DNA (ctDNA) from 70 LA-NSCLC patients receiving definitive radiotherapy/chemoradiotherapy (RT/CRT) with/without immunotherapy. High mmVAFs in pre-treatment tissue biopsies, indicating clonal predominant tumors (P < 0.01), were associated with inferior overall survival [OS, hazard ratio (HR): 1.48, 95 % confidence interval (CI): 1.11-1.98]. Similar associations of mmVAF with clonality (P < 0.01) and OS (HR: 2.24, 95 % CI: 0.71-7.08) were observed in pre-treatment ctDNA. At 1-month post-RT, ctDNA mmVAF-high patients receiving consolidation immunotherapy exhibited improved progression-free survival (PFS) compared to those who did not (HR: 0.14, 95 % CI: 0.03-0.67). From the baseline to week 4 of RT and/or 1-month post-RT, survival benefits from consolidation immunotherapy were exclusively observed in ctDNA mmVAF-increased patients (PFS, HR: 0.39, 95 % CI: 0.14-1.15), especially in terms of distant metastasis (HR: 0.11, 95 % CI: 0.01-0.95). In summary, our longitudinal data demonstrated the applicability of ctDNA-defined clonality for prognostic stratification and immunotherapy benefit prediction in LA-NSCLC.

Tumor heterogeneity: how could we use it to achieve better clinical outcomes?

Differences in tumors related to location, tissue type, and histological subtype have been well documented for decades. Tumors are also molecularly very diverse. In this short review we describe the current classification schemes for tumor heterogeneity. We enlist the various drivers of tumor heterogeneity generation and comment on their clinical significance. New molecular techniques promise to assess tumor heterogeneity at affordable cost, so that these techniques can soon enter the clinic. While tumor heterogeneity currently represents a major unfavorable barrier in the field of oncology, it may also be a key in revolutionizing cancer diagnosis and treatment. Information regarding tumor heterogeneity has the potential to provide more thorough prognostic information, guide more efficacious combination treatment regimens, and lead to the development of novel therapeutic strategies and identification of new targets. For these gains to be realized, assessment of tumor heterogeneity needs to be incorporated into current diagnostic protocols but standardized and reproducible assessment methods are required. Fortunately, when these advances are realized, tumor heterogeneity has the potential to improve clinical outcomes.

Diverse drug delivery systems for the enhancement of cancer immunotherapy: an overview

Despite the clear benefits demonstrated by immunotherapy, there is still an inevitable off-target effect resulting in serious adverse immune reactions. In recent years, the research and development of Drug Delivery System (DDS) has received increased prominence. In decades of development, DDS has demonstrated the ability to deliver drugs in a precisely targeted manner to mitigate side effects and has the advantages of flexible control of drug release, improved pharmacokinetics, and drug distribution. Therefore, we consider that combining cancer immunotherapy with DDS can enhance the anti-tumor ability. In this paper, we provide an overview of the latest drug delivery strategies in cancer immunotherapy and briefly introduce the characteristics of DDS based on nano-carriers (liposomes, polymer nano-micelles, mesoporous silica, extracellular vesicles, etc.) and coupling technology (ADCs, PDCs and targeted protein degradation). Our aim is to show readers a variety of drug delivery platforms under different immune mechanisms, and analyze their advantages and limitations, to provide more superior and accurate targeting strategies for cancer immunotherapy.

Aptamer-Based Recognition of Breast Tumor Cells: A New Era for Breast Cancer Diagnosis

Breast cancer is one of the leading causes of death among women worldwide and can be classified into four major distinct molecular subtypes based on the expression of specific receptors. Despite significant advances, the lack of biomarkers for detailed diagnosis and prognosis remains a major challenge in the field of oncology. This study aimed to identify short single-stranded oligonucleotides known as aptamers to improve breast cancer diagnosis. The Cell-SELEX technique was used to select aptamers specific to the MDA-MB-231 tumor cell line. After selection, five aptamers demonstrated specific recognition for tumor breast cell lines and no binding to non-tumor breast cells. Validation of aptamer specificity revealed recognition of primary and metastatic tumors of all subtypes. In particular, AptaB4 and AptaB5 showed greater recognition of primary tumors and metastatic tissue, respectively. Finally, a computational biology approach was used to identify potential aptamer targets, which indicated that CSKP could interact with AptaB4. These results suggest that aptamers are promising in breast cancer diagnosis and treatment due to their specificity and selectivity.

MRI-Based Interstitial Fluid Velocity Analysis for Drug Delivery Efficiency Evaluation in Tumor

There are many flow behaviors in solid tumors, including intravascular, bloodstream, and interstitial convection. Studies have shown that tumor interstitial fluid (TIF) is an important part of tumor microenvironment regulation and affects drug delivery and metabolism between tumor cells. Magnetic resonance imaging (MRI) is suitable for detecting the flow rates of liquids in tissues. Clinical phase contrast PC-MRI technology has been designed to observe the blood flow in large vessels such as arteries and veins; however, it is not sensitive enough to deal with slow flow velocity. Our previously developed vertical plane echo PC-MRI technology, the Velocity Mapping sequence, improved the signal-to-noise ratio (SNR) for measuring slow interstitial fluid rate. In this study, this sequence was used to determine the TIF flow rate in MDA-MB-231 human breast tumor cells used in BALB/c nude male mice. Two different sizes of contrast agents were intravenously injected, and the relationship between their distribution and the TIF flow rate was studied for the first time. Combining the results of clinical scanning showed that small-molecule DTPA-Gd (diethylenetriaminepentaacetic acid-gadolinium) was distributed immediately around the tumor margin after the injection. This distribution was positively correlated to the high flow rate area of the TIF before administration. In contrast, nanoparticles NaGdF4-PEG (polyethylene glycol) entered the tumor and reached their peak at 3 h. Drug distribution was negatively correlated with the high-flow-rate region of the TIF. Investigation of the TIF velocity can help better understand the fluid behavior in tumors and its role in drug delivery.

Measured Steps: Navigating the Path of Oligoprogressive Lung Cancer with Targeted and Immunotherapies

PURPOSE OF REVIEW

This review discusses the definitions, treatment modalities, management, future directions, and ongoing clinical trials of oligoprogressive disease in oncogene-driven and non-oncogene-driven NSCLC.

RECENT FINDINGS

During the last decades, diagnostic and treatment modalities for oligometastatic NSCLC have advanced significantly, leading to improved survival. Additionally, our understanding of the tumor biology of oligoprogressive disease has expanded. However, despite the efforts of organizations, such as EORTC, ESTRO, and ASTRO proposing definitions for oligometastatic and oligoprogressive disease, heterogeneity in definitions persists in (ongoing) trials. Recognizing the significance of subclassification within oligoprogressive disease in NSCLC and the varying risks associated with subsequent metastatic spread, there is a call for tailored management strategies. A consensus on standardized criteria for the definition of oligoprogressive disease is urgently needed and will not only facilitate meaningful comparisons between studies but also pave the way for the development of personalized treatment plans that take into account the heterogeneous nature of oligoprogressive disease.

The benign nature and rare occurrence of cardiac myxoma as a possible consequence of the limited cardiac proliferative/ regenerative potential: a systematic review

BACKGROUND

Cardiac Myxoma is a primary tumor of heart. Its origins, rarity of the occurrence of primary cardiac tumors and how it may be related to limited cardiac regenerative potential, are not yet entirely known. This study investigates the key cardiac genes/ transcription factors (TFs) and signaling pathways to understand these important questions.

METHODS

Databases including PubMed, MEDLINE, and Google Scholar were searched for published articles without any date restrictions, involving cardiac myxoma, cardiac genes/TFs/signaling pathways and their roles in cardiogenesis, proliferation, differentiation, key interactions and tumorigenesis, with focus on cardiomyocytes.

RESULTS

The cardiac genetic landscape is governed by a very tight control between proliferation and differentiation-related genes/TFs/pathways. Cardiac myxoma originates possibly as a consequence of dysregulations in the gene expression of differentiation regulators including Tbx5, GATA4, HAND1/2, MYOCD, HOPX, BMPs. Such dysregulations switch the expression of cardiomyocytes into progenitor-like state in cardiac myxoma development by dysregulating Isl1, Baf60 complex, Wnt, FGF, Notch, Mef2c and others. The Nkx2-5 and MSX2 contribute predominantly to both proliferation and differentiation of Cardiac Progenitor Cells (CPCs), may possibly serve roles based on the microenvironment and the direction of cell circuitry in cardiac tumorigenesis. The Nkx2-5 in cardiac myxoma may serve to limit progression of tumorigenesis as it has massive control over the proliferation of CPCs. The cardiac cell type-specific genetic programming plays governing role in controlling the tumorigenesis and regenerative potential.

CONCLUSION

The cardiomyocytes have very limited proliferative and regenerative potential. They survive for long periods of time and tightly maintain the gene expression of differentiation genes such as Tbx5, GATA4 that interact with tumor suppressors (TS) and exert TS like effect. The total effect such gene expression exerts is responsible for the rare occurrence and benign nature of primary cardiac tumors. This prevents the progression of tumorigenesis. But this also limits the regenerative and proliferative potential of cardiomyocytes. Cardiac Myxoma develops as a consequence of dysregulations in these key genes which revert the cells towards progenitor-like state, hallmark of CM. The CM development in carney complex also signifies the role of TS in cardiac cells.

Applications of Innovation Technologies for Personalized Cancer Medicine: Stem Cells and Gene-Editing Tools

Personalized medicine is a new approach toward safer and even cheaper treatments with minimal side effects and toxicity. Planning a therapy based on individual properties causes an effective result in a patient's treatment, especially in a complex disease such as cancer. The benefits of personalized medicine include not only early diagnosis with high accuracy but also a more appropriate and effective therapeutic approach based on the unique clinical, genetic, and epigenetic features and biomarker profiles of a specific patient's disease. In order to achieve personalized cancer therapy, understanding cancer biology plays an important role. One of the crucial applications of personalized medicine that has gained consideration more recently due to its capability in developing disease therapy is related to the field of stem cells. We review various applications of pluripotent, somatic, and cancer stem cells in personalized medicine, including targeted cancer therapy, cancer modeling, diagnostics, and drug screening. CRISPR-Cas gene-editing technology is then discussed as a state-of-the-art biotechnological advance with substantial impacts on medical and therapeutic applications. As part of this section, the role of CRISPR-Cas genome editing in recent cancer studies is reviewed as a further example of personalized medicine application.

Simple droplet microfluidics platform for drug screening on cancer spheroids

3D in vitro biological systems are progressively replacing 2D systems to increase the physiological relevance of cellular studies. Microfluidics-based approaches can be powerful tools towards such biomimetic systems, but often require high-end complicated and expensive processes and equipment for microfabrication. Herein, a drug screening platform is proposed, minimizing technicality and manufacturing steps. It provides an alternate way of spheroid generation in droplets in tubes. Droplet microfluidics then elicit multiple droplets merging events at programmable times, to submit sequentially the spheroids to chemotherapy and to reagents for cytotoxicity screening. After a comprehensive study of tumorogenesis within the droplets, the system is validated for drug screening (IC50) with chemotherapies in cancer cell lines as well as cells from a patient-derived-xenografts (PDX). As compared to microtiter plates methods, our system reduces the initial number of cells up to 10 times and opens new avenues towards primary tumors drug screening approaches.

Fusing Positive and Negative CT Contrast Nanoagent for the Sensitive Detection of Hepatoma

Positive computed tomography (CT) contrast nanoagent has significant applications in diagnosing tumors. However, the sensitive differentiation between hepatoma and normal liver tissue remains challenging. This challenge arises primarily because both normal liver and hepatoma tissues capture the nanoagent, resulting in similar positive CT contrasts. Here, a strategy for fusing positive and negative CT contrast nanoagent is proposed to detect hepatoma. A nanoagent Hf-MOF@AB@PVP initially generates a positive CT contrast signal of 120.3 HU in the liver. Subsequently, it can specifically respond to the acidic microenvironment of hepatoma to generate H2 , further achieving a negative contrast of -96.0 HU. More importantly, the relative position between the negative and positive signals area is helpful to determine the location of hepatoma and normal liver tissues. The distinct contrast difference of 216.3 HU and relative orientation between normal liver and tumor tissues are meaningful to sensitively distinguish hepatoma from normal liver tissue utilizing CT imaging.

Detection of isoforms and genomic alterations by high-throughput full-length single-cell RNA sequencing in ovarian cancer

Understanding the complex background of cancer requires genotype-phenotype information in single-cell resolution. Here, we perform long-read single-cell RNA sequencing (scRNA-seq) on clinical samples from three ovarian cancer patients presenting with omental metastasis and increase the PacBio sequencing depth to 12,000 reads per cell. Our approach captures 152,000 isoforms, of which over 52,000 were not previously reported. Isoform-level analysis accounting for non-coding isoforms reveals 20% overestimation of protein-coding gene expression on average. We also detect cell type-specific isoform and poly-adenylation site usage in tumor and mesothelial cells, and find that mesothelial cells transition into cancer-associated fibroblasts in the metastasis, partly through the TGF-β/miR-29/Collagen axis. Furthermore, we identify gene fusions, including an experimentally validated IGF2BP2::TESPA1 fusion, which is misclassified as high TESPA1 expression in matched short-read data, and call mutations confirmed by targeted NGS cancer gene panel results. With these findings, we envision long-read scRNA-seq to become increasingly relevant in oncology and personalized medicine.

Radiological artificial intelligence - predicting personalized immunotherapy outcomes in lung cancer

Personalized medicine has revolutionized approaches to treatment in the field of lung cancer by enabling therapies to be specific to each patient. However, physicians encounter an immense number of challenges in providing the optimal treatment regimen for the individual given the sheer complexity of clinical aspects such as tumor molecular profile, tumor microenvironment, expected adverse events, acquired or inherent resistance mechanisms, the development of brain metastases, the limited availability of biomarkers and the choice of combination therapy. The integration of innovative next-generation technologies such as deep learning-a subset of machine learning-and radiomics has the potential to transform the field by supporting clinical decision making in cancer treatment and the delivery of precision therapies while integrating numerous clinical considerations. In this review, we present a brief explanation of the available technologies, the benefits of using these technologies in predicting immunotherapy response in lung cancer, and the expected future challenges in the context of precision medicine.

The permissive binding theory of cancer

The later stages of cancer, including the invasion and colonization of new tissues, are actively mysterious compared to earlier stages like primary tumor formation. While we lack many details about both, we do have an apparently successful explanatory framework for the earlier stages: one in which genetic mutations hold ultimate causal and explanatory power. By contrast, on both empirical and conceptual grounds, it is not currently clear that mutations alone can explain the later stages of cancer. Can a different type of molecular change do better? Here, I introduce the "permissive binding theory" of cancer, which proposes that novel protein binding interactions are the key causal and explanatory entity in invasion and metastasis. It posits that binding is more abundant at baseline than we observe because it is restricted in normal physiology; that any large perturbation to physiological state revives this baseline abundance, unleashing many new binding interactions; and that a subset of these cause the cellular functions at the heart of oncogenesis, especially invasion and metastasis. Significant physiological perturbations occur in cancer cells in very early stages, and generally become more extreme with progression, providing interactions that continually fuel invasion and metastasis. The theory is compatible with, but not limited to, causal roles for the diverse molecular changes observed in cancer (e.g. gene expression or epigenetic changes), as these generally act causally upstream of proteins, and so may exert their effects by changing the protein binding interactions that occur in the cell. This admits the possibility that molecular changes that appear quite different may actually converge in creating the same few protein complexes, simplifying our picture of invasion and metastasis. If correct, the theory offers a concrete therapeutic strategy: targeting the key novel complexes. The theory is straightforwardly testable by large-scale identification of protein interactions in different cancers.

Good CARMA: Turning bad tumor-resident myeloid cells good with chimeric antigen receptor macrophages

In religious philosophy, the concept of karma represents the effect of one's past and present actions on one's future. Macrophages are highly plastic cells with myriad roles in health and disease. In the setting of cancer, macrophages are among the most plentiful members of the immune microenvironment where they generally support tumor growth and restrain antitumor immunity. However, macrophages are not necessarily born bad. Macrophages or their immediate progenitors, monocytes, are induced to traffic to the tumor microenvironment (TME) and during this process they are polarized toward a tumor-promoting phenotype. Efforts to deplete or repolarize tumor-associated macrophages (TAM) for therapeutic benefit in cancer have to date disappointed. By contrast, genetic engineering of macrophages followed by their transit into the TME may allow these impressionable cells to mend their ways. In this review, we summarize and discuss recent advances in the genetic engineering of macrophages for the treatment of cancer.

Economic Evaluations of Imaging Biomarker-Driven Companion Diagnostics for Cancer: A Systematic Review

INTRODUCTION

There is a boom in imaging biomarker-driven companion and complementary diagnostics (CDx) for cancer, which brings opportunity for personalized medicine. Whether adoption of these technologies is likely to be cost-effective is a relevant question, and studies on this topic are emerging. Despite the growing number of economic evaluations, no review of the methods used, quality of reporting, and potential risk of bias has been done. We report a systematic review to identify, summarize, and critique the cost-effectiveness evidence for the use of biomarker-driven and imaging-based CDx to inform cancer treatments.

METHODS

The Preferred Reporting Items of Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. Systematic literature searches until 30 December 2022 were performed in PubMed, Web of Science, Medline, Embase, and Scopus for economic evaluations of imaging biomarker-based CDx for cancer. The inclusion and exclusion of studies were determined by pre-specified eligibility criteria informed by the 'Patient, Intervention, Comparison, Outcome' (PICO) framework. The Consolidated Health Economic Evaluation Reporting Standards (CHEERS) was used to assess the quality of reporting, and the Bias in Economic Evaluation (ECOBIAS) was used to examine the potential risk of bias of included studies.

RESULTS

A total of 12 papers were included, with eight model-based and four trial-based studies. Implementing biomarker-driven, imaging-based CDx was reported to be cost-effective, cost saving, or dominant (cost saving and more effective) in ten papers. Inconsistent methods were found in the studies, and the quality of reporting was lacking against the CHEERS reporting guideline. Several potential sources of 'risk of bias' were identified. These should be acknowledged and carefully considered by researchers planning future health economic evaluations.

CONCLUSION

Despite favorable results towards the implementation of imaging biomarker-based CDx for cancer, there is room for improvement regarding the quantity and quality of economic evaluations, and that is expected as the awareness of current study limitations increases and more clinical data become available in the future.

Using picoliter droplet deposition to track clonal competition in adherent and organoid cancer cell cultures

Clonal growth and competition underlie processes of key relevance in etiology, progression and therapy response across all cancers. Here, we demonstrate a novel experimental approach, based on multi-color, fluorescent tagging of cell nuclei, in combination with picoliter droplet deposition, to study the clonal dynamics in two- and three-dimensional cell cultures. The method allows for the simultaneous visualization and analysis of multiple clones in individual multi-clonal colonies, providing a powerful tool for studying clonal dynamics and identifying clonal populations with distinct characteristics. Results of our experiments validate the utility of the method in studying clonal dynamics in vitro, and reveal differences in key aspects of clonal behavior of different cancer cell lines in monoculture conditions, as well as in co-cultures with stromal fibroblasts.

Single-cell morphological and topological atlas reveals the ecosystem diversity of human breast cancer

Digital pathology allows computerized analysis of tumor ecosystem using whole slide images (WSIs). Here, we present single-cell morphological and topological profiling (sc-MTOP) to characterize tumor ecosystem by extracting the features of nuclear morphology and intercellular spatial relationship for individual cells. We construct a single-cell atlas comprising 410 million cells from 637 breast cancer WSIs and dissect the phenotypic diversity within tumor, inflammatory and stroma cells respectively. Spatially-resolved analysis identifies recurrent micro-ecological modules representing locoregional multicellular structures and reveals four breast cancer ecotypes correlating with distinct molecular features and patient prognosis. Further analysis with multiomics data uncovers clinically relevant ecosystem features. High abundance of locally-aggregated inflammatory cells indicates immune-activated tumor microenvironment and favorable immunotherapy response in triple-negative breast cancers. Morphological intratumor heterogeneity of tumor nuclei correlates with cell cycle pathway activation and CDK inhibitors responsiveness in hormone receptor-positive cases. sc-MTOP enables using WSIs to characterize tumor ecosystems at the single-cell level.

Radiomic-Based Prediction of Lesion-Specific Systemic Treatment Response in Metastatic Disease

Despite sharing the same histologic classification, individual tumors in multi metastatic patients may present with different characteristics and varying sensitivities to anticancer therapies. In this study, we investigate the utility of radiomic biomarkers for prediction of lesion-specific treatment resistance in multi metastatic leiomyosarcoma patients. Using a dataset of n=202 lung metastases (LM) from n=80 patients with 1648 pre-treatment computed tomography (CT) radiomics features and LM progression determined from follow-up CT, we developed a radiomic model to predict the progression of each lesion. Repeat experiments assessed the relative predictive performance across LM volume groups. Lesion-specific radiomic models indicate up to a 5-fold increase in predictive capacity compared with a no-skill classifier, with an area under the precision-recall curve of 0.79 for the most precise model (FDR = 0.01). Precision varied by administered drug and LM volume. The effect of LM volume was controlled by removing radiomic features at a volume-correlation coefficient threshold of 0.20. Predicting lesion-specific responses using radiomic features represents a novel strategy by which to assess treatment response that acknowledges biological diversity within metastatic subclones, which could facilitate management strategies involving selective ablation of resistant clones in the setting of systemic therapy.

The effect of tumor vascular remodeling and immune microenvironment activation induced by radiotherapy: quantitative evaluation with magnetic resonance/photoacoustic dual-modality imaging

Background

Tumor radiotherapy combined with immunotherapy for solid tumors has been proposed, but tumor vascular structure abnormalities and immune microenvironment often affect the therapeutic effect of tumor, and multimodal imaging technology can provide more accurate and comprehensive information in tumor research. The purpose of this study was to evaluate the dynamic monitoring of tumor blood vessels and microenvironment induced by radiotherapy by magnetic resonance/photoacoustic (MR/PA) imaging, and to explore its application value in radiotherapy combined with immunotherapy.

Methods

The tumor-bearing mice were randomly allocated into six groups, which received different doses of radiation therapy (2 Gy ×14 or 8 Gy ×3) and anti-programmed death ligand-1 (PD-L1) antibody for two consecutive weeks. MR/PA imaging was used to noninvasively evaluate the response of tumor to different doses of radiotherapy, combined with histopathological techniques to observe the tumor vessels and microenvironment.

Results

The inhibitory effect of high-dose radiotherapy on tumors was significantly greater than that of low-dose radiotherapy, with the MR images revealing that the signal intensity decreased significantly (P<0.05). Compared with those in the other groups, the tumor vascular density decreased significantly (P<0.01), and the vascular maturity index increased significantly in the low-dose group (P<0.05). The PA images showed that the deoxyhemoglobin and total hemoglobin levels decreased and the SO2 level increased after radiation treatment (P<0.05). In addition, the high-dose group had an increased number of tumor-infiltrating lymphocytes (CD4+ T and CD8+ T cells) (P<0.01, P<0.05) and natural killer cells (P<0.001) and increased PD-L1 expression in the tumors (P<0.05). The combination of radiotherapy and immunotherapy increased the survival rate of the mice (P<0.05), and a regimen of an 8 Gy dose of radiation combined with immunotherapy inhibited tumor growth and increased the survival rate of the mice to a greater degree than the 2 Gy radiation dose with immunotherapy combination (P=0.002).

Conclusions

Differential fractionation radiotherapy doses exert biological effects on tumor vascular and the immune microenvironment, and MR/PA can be used to evaluate tumor vascular remodeling after radiotherapy, which has certain value for the clinical applications of radiotherapy combined with immunotherapy.

Dynamic contrast-enhanced magnetic resonance imaging radiomics analysis based on intratumoral subregions for predicting luminal and nonluminal breast cancer

Background

Breast cancer is a heterogeneous disease with different morphological and biological characteristics. The molecular subtypes of breast cancer are closely related to the treatment and prognosis of patients. In order to predict the luminal type of breast cancer in a noninvasive manner, our study developed and validated a radiomics nomogram combining clinical factors with a radiomics score based on the features of the intratumoral subregion to distinguish between luminal and nonluminal breast cancer.

Methods

From January 2018 to January 2020, 153 women with clinically and pathologically diagnosed breast cancer with an average age of 50.08 years were retrospectively analyzed. Using a semiautomatic segmentation method, the whole tumor was divided into 3 subregions on the basis of the time required for the contrast agent to reach its peak; 540 features were extracted from 3 subregions and the whole tumor region. Subsequently, 2 machine learning classifiers were developed. The least absolute shrinkage and selection operator method was used for feature selection and radiomics score (Rad-score) construction. Moreover, multivariable logistic regression analysis was applied to select independent factors from the Rad-score and clinical factors to establish a prediction model in the form of a nomogram. The performance of the nomogram was evaluated through calibration, discrimination, and clinical usefulness.

Results

The prediction performance of texture features from the rapid subregion was the best in the 3 intratumoral subregions, and the area under the receiver operating characteristic curve (AUC) values in the training and validation cohort were 0.805 (95% CI: 0.719-0.892) and 0.737 (95% CI: 0.581-0.893), respectively. The Rad-score, consisting of 5 features from the rapid subregion, was associated with the luminal type of breast cancer (P=0.001 and P=0.035 in the training and validation cohorts, respectively). The predictors included in the personalized prediction nomogram included Rad-score, human epidermal growth factor receptor 2 (HER2) status, and tumor histological grade. The nomogram showed good discrimination, with an area under the receiver operating characteristic curve in the training and validation cohorts of 0.830 (95% CI: 0.746-0.896) and 0.879 (95% CI: 0.748-0.957), respectively. The calibration curve of the 2 cohorts and decision curve analysis demonstrated that the nomogram had good calibration and clinical usefulness.

Conclusions

We proposed a nomogram model that combined clinical factors and Rad-score, which showed good performance in predicting the luminal type of breast cancer.

Dual receptor specific nanoparticles targeting EGFR and PD-L1 for enhanced delivery of docetaxel in cancer therapy

Dual-receptor targeted (DRT) nanoparticles which contain two distinct targeting agents may exhibit higher cell selectivity, cellular uptake, and cytotoxicity toward cancer cells than single-ligand targeted nanoparticle systems without additional functionality. The purpose of this study is to prepare DRT poly(lactic-co-glycolic acid) (PLGA) nanoparticles for targeting the delivery of docetaxel (DTX) to the EGFR and PD-L1 receptor positive cancer cells such as human glioblastoma multiform (U87-MG) and human non-small cell lung cancer (A549) cell lines. Anti-EGFR and anti-PD-L1 antibody were decorated on DTX loaded PLGA nanoparticles to prepare DRT-DTX-PLGA via. single emulsion solvent evaporation method. Physicochemical characterizations of DRT-DTX-PLGA, such as particle size, zeta-potential, morphology, and in vitro DTX release were also evaluated. The average particle size of DRT-DTX-PLGA was 124.2 ± 1.1 nm with spherical and smooth morphology. In the cellular uptake study, the DRT-DTX-PLGA endocytosed by the U87-MG and A549 cells was single ligand targeting nanoparticle. From the in vitro cell cytotoxicity, and apoptosis studies, we reported that DRT-DTX-PLGA exhibited high cytotoxicity and enhanced the apoptotic cell compared to the single ligand-targeted nanoparticle. The dual receptor mediated endocytosis of DRT-DTX-PLGA showed a high binding affinity effect that leads to high intracellular DTX concentration and exhibited high cytotoxic properties. Thus, DRT nanoparticles have the potential to improve cancer therapy by providing selectivity over single-ligand-targeted nanoparticles.