Clinical implications of intratumor heterogeneity: challenges and opportunities

The potential roles of HIF-1α in epithelial-mesenchymal transition and ferroptosis in tumor cells

In tumors, the rapid proliferation of cells and the imperfect blood supply system lead to hypoxia, which can regulate the adaptation of tumor cells to the hypoxic environment through hypoxia-inducible factor-1α (HIF-1α) and promote tumor development in multiple ways. Recent studies have found that epithelial-mesenchymal transition (EMT) and ferroptosis play important roles in the progression of tumor cells. The activation of HIF-1α is considered a key factor in inducing EMT in tumor cells. When HIF-1α is activated, it can regulate EMT-related genes, causing tumor cells to gradually lose their epithelial characteristics and acquire more invasive mesenchymal traits. The occurrence of EMT allows tumor cells to better adapt to changes in the surrounding tissue, enhancing their migratory and invasive capabilities, thus promoting tumor progression. At the same time, HIF-1α also plays a crucial regulatory role in ferroptosis in tumor cells. In a hypoxic environment, HIF-1α may affect processes such as iron metabolism and oxidative stress responses, inducing ferroptosis in tumor cells. This article briefly reviews the dual role of HIF-1α in EMT and ferroptosis in tumor cells, helping to gain a deeper understanding of the regulatory pathways of HIF-1α in the development of tumor cells, providing a new perspective for understanding the pathogenesis of tumors. The regulation of HIF-1α may become an important strategy for future tumor therapy.

In silico evaluation of potential breast cancer receptor antagonists from GC-MS and HPLC identified compounds in Pleurotus ostreatus extracts

Introduction: Pharmacotherapeutic targets for breast cancer include the estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor (EGFR). Inhibitors of these receptors could be interesting therapeutic candidates for the treatment and management of breast cancer (BC). Aim: This study used GC-MS and HPLC to identify bioactive compounds in Pleurotus ostreatus (P. ostreatus) extracts and applied in silico methods to identify potent EGFR, ER, and PR inhibitors from the compounds as potential drug candidates. Method: GC-MS and HPLC were used to identify bioactive chemicals in P. ostreatus extracts of aqueous (PO-A), methanol (PO-M), ethanol (PO-E), chloroform (PO-C), and n-hexane (PO-H). The ER, PR, and EGFR model optimization and molecular docking of compounds/control inhibitors in the binding pocket were simulated using AutoDock Vina in PyRx. The drug-likeness, pharmacokinetic, and pharmacodynamic features of prospective docking leads were all anticipated. Result: The results indicated the existence of 29 compounds in PO-A, 36 compounds in PO-M and PO-E, 42 compounds in PO-C, and 22 compounds in PO-H extracts. With ER, only o-tolylamino-acetic acid (4-nitro-benzylidene)-hydrazide (-7.5 kcal mol-1) from the ethanolic extract could bind to the receptor. PR and EGFR, on the other hand, identified several compounds with higher binding affinities than the control. Ergotaman-3',6',18-trione (-8.1 kcal mol-1), 5,10-diethoxy-2,3,7,8-tetrahydro-1H,6H-dipyrrolo[1,2-a:1',2'-d]pyrazine (-7.8 kcal mol-1) from the aqueous extract; o-tolylamino-acetic acid (4-nitro-benzylidene)-hydrazide (-8.4 kcal mol-1) from the ethanolic extract had better binding affinity compared to progesterone (-7.7 kcal mol-1). Likewise, ergotaman-3',6',18-trione (-9.7 kcal mol-1) from the aqueous extract and phenol, 2,4-bis(1,1-dimethyl ethyl) (-8.2 kcal mol-1) from the chloroform extract had better binding affinities compared to the control, gefitinib (-7.9 kcal mol-1) with regards to EGFR. None of the PO-H or PO-M extracts outperformed the control for any of the proteins. Phenols and flavonoids such as quercetin, luteolin, rutin, chrysin, apigenin, ellagic acid, and naringenin had better binding affinity to PR and EGFR compared to their control. Conclusion: The identified compounds in the class of phenols and flavonoids were better lead molecules due to their ability to strongly bind to the proteins' receptors. These compounds showed promising drug-like properties; they could be safe and new leads for creating anticancer medicines.

Spatial intra-tumour heterogeneity and treatment-induced genomic evolution in oesophageal adenocarcinoma: implications for prognosis and therapy

BACKGROUND

Oesophageal adenocarcinoma (OAC) is a highly heterogeneous cancer with poor survival. Standard curative treatment is chemotherapy with or without radiotherapy followed by oesophagectomy. Genomic heterogeneity is a feature of OAC and has been linked to treatment resistance.

METHODS

Whole-genome sequencing data from 59 treatment-naïve and 18 post-treatment samples from 29 OAC patients was analysed. Twenty-seven of these were enrolled in the DOCTOR trial, sponsored by the Australasian Gastro-Intestinal Trials Group. Two biopsies from each treatment-naïve tumour were assessed to define 'shared' (between both samples) and 'private' (present in one sample) mutations.

RESULTS

Mutational signatures SBS2/13 (APOBEC) and SBS3 (BRCA) were almost exclusively detected in private mutation populations of treatment-naïve tumours. Patients presenting these signatures had significantly worse disease specific survival. Furthermore, mutational signatures associated with platinum-based chemotherapy treatment as well as high platinum enrichment scores were only detected in post-treatment samples. Additionally, clones with high putative neoantigen binding scores were detected in some treatment-naïve samples suggesting immunoediting of clones.

CONCLUSIONS

This study demonstrates the high intra-tumour heterogeneity in OAC, as well as indicators for treatment-induced changes during tumour evolution. Intra-tumour heterogeneity remains a problem for successful treatment strategies in OAC.

The Epigenetic Modifiers HDAC2 and HDAC7 Inversely Associate with Cancer Stemness and Immunity in Solid Tumors

Dysregulation of histone deacetylases (HDACs) is closely associated with cancer development and progression. Here, we comprehensively analyzed the association between all HDAC family members and several clinicopathological and molecular traits of solid tumors across 22 distinct tumor types, focusing primarily on cancer stemness and immunity. To this end, we used publicly available TCGA data and several bioinformatic tools (i.e., GEPIA2, TISIDB, GSCA, Enrichr, GSEA). Our analyses revealed that class I and class II HDAC proteins are associated with distinct cancer phenotypes. The transcriptomic profiling indicated that class I HDAC members, including HDAC2, are positively associated with cancer stemness, while class IIA HDAC proteins, represented by HDAC7, show a negative correlation to cancer stem cell-like phenotypes in solid tumors. In contrast to tumors with high amounts of HDAC7 proteins, the transcriptome signatures of HDAC2-overexpressing cancers are significantly enriched with biological terms previously determined as stemness-associated genes. Moreover, high HDAC2-expressing tumors are depleted with immune-related processes, and HDAC2 expression correlates with tumor immunosuppressive microenvironments. On the contrary, HDAC7 upregulation is significantly associated with enhanced immune responses, followed by enriched infiltration of CD4+ and CD8+ T cells. This is the first comprehensive report demonstrating robust and versatile associations between specific HDAC family members, cancer dedifferentiation, and anti-tumor immune statuses in solid tumors.

Spatial correlation between in vivo imaging and immunohistochemical biomarkers: A methodological study

In this study, we present a method that enables voxel-by-voxel comparison of in vivo imaging to immunohistochemistry (IHC) biomarkers. As a proof of concept, we investigated the spatial correlation between dynamic contrast enhanced (DCE-)CT parameters and IHC biomarkers Ki-67 (proliferation), HIF-1α (hypoxia), and CD45 (immune cells). 54 whole-mount tumor slices of 15 laryngeal and hypopharyngeal carcinomas were immunohistochemically stained and digitized. Heatmaps of biomarker positivity were created and registered to DCE-CT parameter maps. The adiabatic approximation to the tissue homogeneity model was used to fit the following DCE parameters: Ktrans (transfer constant), Ve (extravascular and extracellular space), and Vi (intravascular space). Both IHC and DCE maps were downsampled to 4 × 4 × 3 mm[3] voxels. The mean values per tumor were used to calculate the between-subject correlations between parameters. For the within-subject (spatial) correlation, values of all voxels within a tumor were compared using the repeated measures correlation (rrm). No between-subject correlations were found between IHC biomarkers and DCE parameters, whereas we found multiple significant within-subject correlations: Ve and Ki-67 (rrm = -0.17, P < .001), Ve and HIF-1α (rrm = -0.12, P < .001), Ktrans and CD45 (rrm = 0.13, P < .001), Vi and CD45 (rrm = 0.16, P < .001), and Vi and Ki-67 (rrm = 0.08, P = .003). The strongest correlation was found between IHC biomarkers Ki-67 and HIF-1α (rrm = 0.35, P < .001). This study shows the technical feasibility of determining the 3 dimensional spatial correlation between histopathological biomarker heatmaps and in vivo imaging. It also shows that between-subject correlations do not reflect within-subject correlations of parameters.

Unveiling the role of TAGLN2 in glioblastoma: From proneural-mesenchymal transition to Temozolomide resistance

Glioblastoma (GBM) presents a daunting challenge due to its resistance to temozolomide (TMZ), a hurdle exacerbated by the proneural-to-mesenchymal transition (PMT) from a proneural (PN) to a mesenchymal (MES) phenotype. TAGLN2 is prominently expressed in GBM, particularly in the MES subtype compared to low-grade glioma (LGG) and the PN subtype. Our research reveals TAGLN2's involvement in PMT and TMZ resistance through a series of in vitro and in vivo experiments. TAGLN2 knockdown can restrain proliferation and invasion, trigger DNA damage and apoptosis, and heighten TMZ sensitivity in GBM cells. Conversely, elevating TAGLN2 levels amplifies resistance to TMZ in cellular and intracranial xenograft mouse models. We demonstrate the interaction relationship between TAGLN2 and ERK1/2 through co-immunoprecipitation (Co-IP) and liquid chromatography-tandem mass spectrometry (LC-MS/MS) spectrometry analysis. Knockdown of TAGLN2 results in a decrease in the expression of p-ERK1/2, whereas overexpression of TAGLN2 leads to an increase in p-ERK1/2 expression within the nucleus. Subsequently, the regulatory role of TAGLN2 in the expression and control of MGMT has been demonstrated. Finally, the regulation of TAGLN2 by NF-κB has been validated through chromatin immunoprecipitation and ChIP-PCR assays. In conclusion, our results confirm that TAGLN2 exerts its biological functions by interacting with the ERK/MGMT axis and being regulated by NF-κB, thereby facilitating the acquisition of promoting PMT and increased resistance to TMZ therapy in glioblastoma. These results provide valuable insights for the advancement of targeted therapeutic approaches to overcome TMZ resistance in clinical treatments.

CHNet: A multi-task global-local Collaborative Hybrid Network for KRAS mutation status prediction in colorectal cancer

Accurate prediction of Kirsten rat sarcoma (KRAS) mutation status is crucial for personalized treatment of advanced colorectal cancer patients. However, despite the excellent performance of deep learning models in certain aspects, they often overlook the synergistic promotion among multiple tasks and the consideration of both global and local information, which can significantly reduce prediction accuracy. To address these issues, this paper proposes an innovative method called the Multi-task Global-Local Collaborative Hybrid Network (CHNet) aimed at more accurately predicting patients' KRAS mutation status. CHNet consists of two branches that can extract global and local features from segmentation and classification tasks, respectively, and exchange complementary information to collaborate in executing these tasks. Within the two branches, we have designed a Channel-wise Hybrid Transformer (CHT) and a Spatial-wise Hybrid Transformer (SHT). These transformers integrate the advantages of both Transformer and CNN, employing cascaded hybrid attention and convolution to capture global and local information from the two tasks. Additionally, we have created an Adaptive Collaborative Attention (ACA) module to facilitate the collaborative fusion of segmentation and classification features through guidance. Furthermore, we introduce a novel Class Activation Map (CAM) loss to encourage CHNet to learn complementary information between the two tasks. We evaluate CHNet on the T2-weighted MRI dataset, and achieve an accuracy of 88.93% in KRAS mutation status prediction, which outperforms the performance of representative KRAS mutation status prediction methods. The results suggest that our CHNet can more accurately predict KRAS mutation status in patients via a multi-task collaborative facilitation and considering global-local information way, which can assist doctors in formulating more personalized treatment strategies for patients.

Polyploidy of MDA-MB-231 cells drives increased extravasation with enhanced cell-matrix adhesion

Metastasis, the leading cause of cancer-related deaths, involves a complex cascade of events, including extravasation. Despite extensive research into metastasis, the mechanisms underlying extravasation remain unclear. Molecular targeted therapies have advanced cancer treatment, yet their efficacy is limited, prompting exploration into novel therapeutic targets. Here, we showed the association of polyploidy in MDA-MB-231 breast cancer cells and their extravasation, using microfluidic systems to reproduce the in vivo microvascular environment. We observed enhanced extravasation in polyploid cells alongside upregulated expression of genes involved in cell-substrate adhesion and cell mechanical dynamics. These findings offer insights into the relationship between polyploidy and extravasation, highlighting potential targets for cancer therapy.

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

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

Synchronous Endometrial and Ovarian Endometrioid Carcinoma With MUTYH Germline Mutation: A Case Report With Genetic Analysis

Synchronous endometrial and ovarian endometrioid carcinoma, which simultaneously involves the endometrium and ovary, is a relatively rare entity among gynecological cancers. Precise diagnosis and risk stratification are crucial for disease management. We present a unique case of a 40-year-old woman diagnosed with synchronous endometrial and ovarian endometrioid carcinoma carrying a monoallelic pathogenic MUTYH germline variant. Despite the histological morphology of the right ovarian tumor exhibiting some differences compared to the uterine tumor, we identified three identical somatic mutations shared between the uterine tumor and right ovarian tumor, along with four additional mutations exclusive to the uterine tumor, through the utilization of massively parallel sequencing of a 196-gene panel. These findings enabled us to elucidate the clonal relatedness and potential clonal evolution of the tumor across the two anatomical sites. Furthermore, in accordance with the 2023 FIGO staging system, the patient was diagnosed with Stage IIIB2 uterine cancer, and consequently, adjuvant radiation and chemotherapy were administered after surgery. She is being followed periodically and is normal 15 months after surgery. To the best of our knowledge, this study presents the first case of a patient with synchronous endometrial and ovarian endometrioid carcinoma harboring a monoallelic pathogenic MUTYH germline variant.

CDK7/CDK9 mediates transcriptional activation to prime paraptosis in cancer cells

BACKGROUND

Paraptosis is a programmed cell death characterized by cytoplasmic vacuolation, which has been explored as an alternative method for cancer treatment and is associated with cancer resistance. However, the mechanisms underlying the progression of paraptosis in cancer cells remain largely unknown.

METHODS

Paraptosis-inducing agents, CPYPP, cyclosporin A, and curcumin, were utilized to investigate the underlying mechanism of paraptosis. Next-generation sequencing and liquid chromatography-mass spectrometry analysis revealed significant changes in gene and protein expressions. Pharmacological and genetic approaches were employed to elucidate the transcriptional events related to paraptosis. Xenograft mouse models were employed to evaluate the potential of paraptosis as an anti-cancer strategy.

RESULTS

CPYPP, cyclosporin A, and curcumin induced cytoplasmic vacuolization and triggered paraptosis in cancer cells. The paraptotic program involved reactive oxygen species (ROS) provocation and the activation of proteostatic dynamics, leading to transcriptional activation associated with redox homeostasis and proteostasis. Both pharmacological and genetic approaches suggested that cyclin-dependent kinase (CDK) 7/9 drive paraptotic progression in a mutually-dependent manner with heat shock proteins (HSPs). Proteostatic stress, such as accumulated cysteine-thiols, HSPs, ubiquitin-proteasome system, endoplasmic reticulum stress, and unfolded protein response, as well as ROS provocation primarily within the nucleus, enforced CDK7/CDK9-Rpb1 (RNAPII subunit B1) activation by potentiating its interaction with HSPs and protein kinase R in a forward loop, amplifying transcriptional regulation and thereby exacerbating proteotoxicity leading to initiate paraptosis. The xenograft mouse models of MDA-MB-231 breast cancer and docetaxel-resistant OECM-1 head and neck cancer cells further confirmed the induction of paraptosis against tumor growth.

CONCLUSIONS

We propose a novel regulatory paradigm in which the activation of CDK7/CDK9-Rpb1 by nuclear proteostatic stress mediates transcriptional regulation to prime cancer cell paraptosis.

ProDiv: Prototype-driven consistent pseudo-bag division for whole-slide image classification

BACKGROUND AND OBJECTIVE

Pathology image classification is one of the most essential auxiliary processes in cancer diagnosis. To overcome the problem of inadequate Whole-Slide Image (WSI) samples with weak labels, pseudo-bag-based multiple instance learning (MIL) methods have attracted wide attention in pathology image classification. In this type of method, the division scheme of pseudo-bags is usually a primary factor affecting classification performance. In order to improve the division of WSI pseudo-bags on existing random/clustering approaches, this paper proposes a new Prototype-driven Division (ProDiv) scheme for the pseudo-bag-based MIL classification framework on pathology images.

METHODS

This scheme first designs an attention-based method to generate a bag prototype for each slide. On this basis, it further groups WSI patch instances into a series of instance clusters according to the feature similarities between the prototype and patches. Finally, pseudo-bags are obtained by randomly combining the non-overlapping patch instances of different instance clusters. Moreover, the design scheme of our ProDiv considers practicality, and it could be smoothly assembled with almost all the MIL-based WSI classification methods in recent years.

RESULTS

Empirical results show that our ProDiv, when integrated with several existing methods, can deliver classification AUC improvements of up to 7.3% and 10.3%, respectively on two public WSI datasets.

CONCLUSIONS

ProDiv could almost always bring obvious performance improvements to compared MIL models on typical metrics, which suggests the effectiveness of our scheme. Experimental visualization also visually interprets the correctness of the proposed ProDiv.

Chromatin as an old and new anticancer target

Recent genome-wide analyses identified chromatin modifiers as one of the most frequently mutated classes of genes across all cancers. However, chemotherapies developed for cancers involving DNA damage remain the standard of care for chromatin-deranged malignancies. In this review we address this conundrum by establishing the concept of 'chromatin damage': the non-genetic damage to protein-DNA interactions induced by certain small molecules. We highlight anthracyclines, a class of chemotherapeutic agents ubiquitously applied in oncology, as an example of overlooked chromatin-targeting agents. We discuss our current understanding of this phenomenon and explore emerging chromatin-damaging agents as a basis for further studies to maximize their impact in modern cancer treatment.

Multiparametric MRI for characterization of the tumour microenvironment

Our understanding of tumour biology has evolved over the past decades and cancer is now viewed as a complex ecosystem with interactions between various cellular and non-cellular components within the tumour microenvironment (TME) at multiple scales. However, morphological imaging remains the mainstay of tumour staging and assessment of response to therapy, and the characterization of the TME with non-invasive imaging has not yet entered routine clinical practice. By combining multiple MRI sequences, each providing different but complementary information about the TME, multiparametric MRI (mpMRI) enables non-invasive assessment of molecular and cellular features within the TME, including their spatial and temporal heterogeneity. With an increasing number of advanced MRI techniques bridging the gap between preclinical and clinical applications, mpMRI could ultimately guide the selection of treatment approaches, precisely tailored to each individual patient, tumour and therapeutic modality. In this Review, we describe the evolving role of mpMRI in the non-invasive characterization of the TME, outline its applications for cancer detection, staging and assessment of response to therapy, and discuss considerations and challenges for its use in future medical applications, including personalized integrated diagnostics.

Stratification of glioma based on stemness scores in bulk and single-cell transcriptomes

BACKGROUND

Brain tumours are known to have a high mortality and morbidity rate due to their localised and frequent invasive growth. The concept that glioma resistance could originate from the dissimilarity in the vulnerability of clonogenic glial stem cells to chemotherapeutic drugs and radiation has driven the scientific community to reexamine the comprehension of glioma growth and strategies that target these cells or modify their stemness.

METHODS

Based on the enrichment scores of 12 stemness signatures, we identified glioma subtypes in both tumour bulks and single cells by clustering analysis. Furthermore, we comprehensively compared molecular and clinical features among the glioma subtypes.

RESULTS

Consistently, in seven different datasets, hierarchical clustering uncovered three subtypes of glioma, termed Stem-H, Stem-M, and Stem-L, with high, medium, and low stemness signatures, respectively. Stem-H and Stem-L exhibited the most unfavorable and favourable overall and disease-free survival, respectively. Stem-H showed the highest enrichment scores of the EMT, invasion, proliferation, differentiation, and metastasis processes signatures, while Stem-L displayed the lowest. Stem-H harboured a greater proportion of late-stage tumours compared to Stem-L. Moreover, Stem-H manifested higher tumour mutation burden, DNA damage repair and cell cycle activity, intratumour heterogeneity, and a more frequent incidence of TP53 and EGFR mutations than Stem-L. In contrast, Stem-L had higher O6-Methylguanine-DNA Methyltransferase (MGMT) methylation levels.

CONCLUSION

The classification of glioma based on stemness may offer new insights into the biology of the tumour, as well as more accurate clinical management of the disease.

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.

The future of cancer therapy: exploring the potential of patient-derived organoids in drug development

Cancer therapy is on the brink of a significant transformation with the inclusion of patient-derived organoids (PDOs) in drug development. These three-dimensional cell cultures, directly derived from a patient's tumor, accurately replicate the complex structure and genetic makeup of the original cancer. This makes them a promising tool for advancing oncology. In this review, we explore the practical applications of PDOs in clinical drug screening and pharmacognostic assessment, as well as their role in refining therapeutic strategies. We provide insights into the latest advancements in PDO technology and its implications for predicting treatment responses and facilitating novel drug discoveries. Additionally, we address the operational challenges associated with incorporating PDOs into the drug development process, such as scaling up organoid cultures, ensuring consistent results, and addressing the ethical use of patient-derived materials. Aimed at researchers, clinicians, and key stakeholders in oncology, this article aims to succinctly present both the extraordinary potential and the obstacles to integrating PDOs, thereby shedding light on their prospective impact on the future of cancer treatment.

Integrated proteomics spotlight the proteasome as a therapeutic vulnerability in embryonal tumors with multilayered rosettes

BACKGROUND

Embryonal tumors with multilayered rosettes (ETMR) are rare malignant embryonal brain tumors. The prognosis of ETMR is poor and novel therapeutic approaches are desperately needed. Comprehension of ETMR tumor biology is currently based on only few previous molecular studies, which mainly focused on the analyses of nucleic acids. In this study, we explored integrated ETMR proteomics.

METHODS

Using mass spectrometry, proteome data were acquired from 16 ETMR and the ETMR cell line BT183. Proteome data were integrated with case-matched global DNA methylation data, publicly available transcriptome data, and proteome data of further embryonal and pediatric brain tumors.

RESULTS

Proteome-based cluster analyses grouped ETMR samples according to histomorphology, separating neuropil-rich tumors with neuronal signatures from primitive tumors with signatures relating to stemness and chromosome organization. Integrated proteomics showcased that ETMR and BT183 cells harbor proteasome regulatory proteins in abundance, implicating their strong dependency on the proteasome machinery to safeguard proteostasis. Indeed, in vitro assays using BT183 highlighted that ETMR tumor cells are highly vulnerable toward treatment with the CNS penetrant proteasome inhibitor Marizomib.

CONCLUSIONS

In summary, histomorphology stipulates the proteome signatures of ETMR, and proteasome regulatory proteins are pervasively abundant in these tumors. As validated in vitro, proteasome inhibition poses a promising therapeutic option in ETMR.

The potential role of circular RNAs -regulated PI3K signaling in non-small cell lung cancer: Molecular insights and clinical perspective

Non-small cell lung cancer (NSCLC), accounting for more than 80% of all cases, is the predominant form of lung cancer and the leading cause of cancer-related deaths worldwide. Significant progress has been made in diagnostic techniques, surgical interventions, chemotherapy protocols, and targeted therapies at the molecular level, leading to enhanced treatment outcomes in patients with NSCLC. Extensive evidence supports the use of circular RNAs (circRNAs), a specific category of naturally occurring non-coding small RNAs (ncRNAs), for the diagnosis, monitoring of treatment efficacy, and assessment of survival in NSCLC. CircRNAs have been identified to play significant roles in various aspects of cancer formation, either as tumor suppressors or tumor promoters, contributing to cancer development through several signaling pathways, including the phosphoinositide 3-kinases (PI3Ks) pathway. This pathway is well-established because of its regulatory role in essential cellular processes. CircRNAs regulate the PI3K/AKT pathway by targeting diverse cellular elements. This review aims to provide insight into the involvement of several circRNAs linked to the PI3K/AKT pathway in NSCLC.

NTRK3 exhibits a pro-oncogenic function in upper tract urothelial carcinomas

Neurotrophic receptor tyrosine kinase 3 (NTRK3) has pleiotropic functions: it acts not only as an oncogene in breast and gastric cancers but also as a dependence receptor in tumor suppressor genes in colon cancer and neuroblastomas. However, the role of NTRK3 in upper tract urothelial carcinoma (UTUC) is not well documented. This study investigated the association between NTRK3 expression and outcomes in UTUC patients and validated the results in tests on UTUC cell lines. A total of 118 UTUC cancer tissue samples were examined to evaluate the expression of NTRK3. Survival curves were generated using Kaplan-Meier estimates, and Cox regression models were used for investigating survival outcomes. Higher NTRK3 expression was correlated with worse progression-free survival, cancer-specific survival, and overall survival. Moreover, the results of an Ingenuity Pathway Analysis suggested that NTRK3 may interact with the PI3K-AKT-mTOR signaling pathway to promote cancer. NTRK3 downregulation in BFTC909 cells through shRNA reduced cellular migration, invasion, and activity in the AKT-mTOR pathway. Furthermore, the overexpression of NTRK3 in UM-UC-14 cells promoted AKT-mTOR pathway activity, cellular migration, and cell invasion. From these observations, we concluded that NTRK3 may contribute to aggressive behaviors in UTUC by facilitating cell migration and invasion through its interaction with the AKT-mTOR pathway and the expression of NTRK3 is a potential predictor of clinical outcomes in cases of UTUC.

Identification and classification of glioma subtypes based on RNA-binding proteins

BACKGROUND

Glioma is a common and aggressive primary malignant cancer known for its high morbidity, mortality, and recurrence rates. Despite this, treatment options for glioma are currently restricted. The dysregulation of RBPs has been linked to the advancement of several types of cancer, but their precise role in glioma evolution is still not fully understood. This study sought to investigate how RBPs may impact the development and prognosis of glioma, with potential implications for prognosis and therapy.

METHODS

RNA-seq profiles of glioma and corresponding clinical data from the CGGA database were initially collected for analysis. Unsupervised clustering was utilized to identify crucial tumor subtypes in glioma development. Subsequent time-series analysis and MS model were employed to track the progression of these identified subtypes. RBPs playing a significant role in glioma progression were then pinpointed using WGCNA and Lasso Cox regression models. Functional analysis of these key RBP-related genes was conducted through GSEA. Additionally, the CIBERSORT algorithm was utilized to estimate immune infiltrating cells, while the STRING database was consulted to uncover potential mechanisms of the identified biomarkers.

RESULTS

Six tumor subgroups were identified and found to be highly homogeneous within each subgroup. The progression stages of these tumor subgroups were determined using time-series analysis and a MS model. Through WGCNA, Lasso Cox, and multivariate Cox regression analysis, it was confirmed that BCLAF1 is correlated with survival in glioma patients and is closely linked to glioma progression. Functional annotation suggests that BCLAF1 may impact glioma progression by influencing RNA splicing, which in turn affects the cell cycle, Wnt signaling pathway, and other cancer development pathways.

CONCLUSIONS

The study initially identified six subtypes of glioma progression and assessed their malignancy ranking. Furthermore, it was determined that BCLAF1 could serve as an RBP-related prognostic marker, offering significant implications for the clinical diagnosis and personalized treatment of glioma.

Molecular Heterogeneity in Leiomyosarcoma and Implications for Personalised Medicine

OPINION STATEMENT

Leiomyosarcoma (LMS) is one of the more common subtypes of soft tissue sarcomas (STS), accounting for about 20% of cases. Differences in anatomical location, risk of recurrence and histomorphological variants contribute to the substantial clinical heterogeneity in survival outcomes and therapy responses observed in patients. There is therefore a need to move away from the current one-size-fits-all treatment approach towards a personalised strategy tailored for individual patients. Over the past decade, tissue profiling studies have revealed key genomic features and an additional layer of molecular heterogeneity among patients, with potential utility for optimal risk stratification and biomarker-matched therapies. Furthermore, recent studies investigating intratumour heterogeneity and tumour evolution patterns in LMS suggest some key features that may need to be taken into consideration when designing treatment strategies and clinical trials. Moving forward, national and international collaborative efforts to aggregate expertise, data, resources and tools are needed to achieve a step change in improving patient survival outcomes in this disease of unmet need.

Niclosamide: A career builder

My contribution to honoring Professor Kinam Park celebrates and resonates with his scholarly career in drug delivery, his commitment to encouraging the next generation(s), and his efforts to keep us focused on clinically effective formulations. To do this I take as my example, niclosamide, a small molecule protonophore that, uniquely, can "target" all cell membranes, both plasma and organelle. As such, it acts upstream of many cell pathways and so has the potential to affect many of the essential events that a cell, and particularly a diseased cell or other entities like a virus, use to stay alive and prosper. Literature shows that it has so far been discovered to positively influence (at least): cancer, bacterial and viral infection, metabolic diseases such as Type II diabetes, NASH and NAFLD, artery constriction, endometriosis, neuropathic pain, rheumatoid arthritis, sclerodermatous graft-versus-host disease, systemic sclerosis, Parkinson's, and COPD. With such a fundamental action and broad-spectrum activity, I believe that studying niclosamide in all its manifestations, discovering if and to what extent it can contribute positively to disease control (and also where it can't), formulating it as effective therapeutics, and testing them in preclinical and clinical trials is a career builder for our next generation(s). The article is divided into two parts: Part I introduces niclosamide and other proton shunts mainly in cancer and viral infections and reviews an exponentially growing literature with some concepts and physicochemical properties that lead to its proton shunt mechanism. Part II focuses on repurposing by reformulation of niclosamide. I give two examples of "carrier-free formulations", - one for cancer (as a prodrug therapeutic of niclosamide stearate for i.v. and other administration routes, exemplified by our recent work on Osteosarcoma in mice and canine patients), and the other as a niclosamide solution formulation (that could provide the basis for a preventative nasal spray and early treatment option for COVID19 and other respiratory virus infections). My goal is to excite and enthuse, encourage, and motivate all involved in the drug development and testing process in academia, institutes, and industry, to learn more about this interesting molecule and others like it. To enable such endeavors, I give many proposed ideas throughout the document, that have been stimulated and inspired by gaps in the literature, urgent needs in disease, and new studies arising from our own work. The hope is that, by reading through this document and studying the suggested topics and references, the drug delivery and development community will continue our lineage and benefit from our legacy to achieve niclosamide's potential as an effective contributor to the treatment and control of many diseases and conditions.

Revolutionizing bone tumor management: cutting-edge breakthroughs in limb-saving treatments

Limb salvage surgery has revolutionized the approach to bone tumors in orthopedic oncology, steering away from historical amputations toward preserving limb function and enhancing patient quality of life. This transformative shift underscores the delicate balance between tumor eradication and optimal postoperative function. Primary and metastatic bone tumors present challenges in early detection, differentiation between benign and malignant tumors, preservation of function, and the risk of local recurrence. Conventional methods, including surgery, radiation therapy, chemotherapy, and targeted therapies, have evolved with a heightened focus on personalized medicine. A groundbreaking development in limb salvage surgery is the advent of 3D-printed patient-specific implants, which significantly enhance anatomical precision, stability, and fixation. These implants reduce soft tissue disruption and the associated risks, fostering improved osseointegration and correction of deformities for a more natural and functional postoperative outcome. Biological and molecular research has reshaped the understanding of bone tumors, guiding surgical interventions with advancements such as genomic profiling, targeted intraoperative imaging, precision targeting of molecular pathways, and immunotherapy tailored to individual tumor characteristics. In the realm of imaging technologies, MRI, CT scans, and intraoperative navigation systems have redefined preoperative planning, minimizing collateral damage and optimizing outcomes through accurate resections. Postoperative rehabilitation plays a crucial role in restoring function and improving the quality of life. Emphasizing early mobilization, effective pain management, and a multidisciplinary approach, rehabilitation addresses the physical, psychological, and social aspects of recovery. Looking ahead, future developments may encompass advanced biomaterials, smart implants, AI algorithms, robotics, and regenerative medicine. Challenges lie in standardization, cost-effectiveness, accessibility, long-term outcome assessment, mental health support, and fostering global collaboration. As research progresses, limb salvage surgery emerges not just as a preservation tool but as a transformative approach, restoring functionality, resilience, and hope in the recovery journey. This review summarizes the recent advances in limb salvage therapy for bone tumors over the past decade.

Precision Medicine in Veterinary Science

Precision medicine focuses on the clinical management of the individual patient, not on population-based findings. Successes from human precision medicine inform veterinary oncology. Early evidence of success for canines shows how precision medicine can be integrated into practice. Decreasing genomic profiling costs will allow increased utilization and subsequent improvement of knowledge base from which to make better informed decisions. Utility of precision medicine in canine oncology will only increase for improved cancer characterization, enhanced therapy selection, and overall more successful management of canine cancer. As such, practitioners are called to interpret and leverage precision medicine reports for their patients.

Modeling Melanoma Heterogeneity In Vitro: Redox, Resistance and Pigmentation Profiles

Microenvironment and transcriptional plasticity generate subpopulations within the tumor, and the use of BRAF inhibitors (BRAFis) contributes to the rise and selection of resistant clones. We stochastically isolated subpopulations (C1, C2, and C3) from naïve melanoma and found that the clones demonstrated distinct morphology, phenotypic, and functional profiles: C1 was less proliferative, more migratory and invasive, less sensitive to BRAFis, less dependent on OXPHOS, more sensitive to oxidative stress, and less pigmented; C2 was more proliferative, less migratory and invasive, more sensitive to BRAFis, less sensitive to oxidative stress, and more pigmented; and C3 was less proliferative, more migratory and invasive, less sensitive to BRAFis, more dependent on OXPHOS, more sensitive to oxidative stress, and more pigmented. Hydrogen peroxide plays a central role in oxidative stress and cell signaling, and PRDXs are one of its main consumers. The intrinsically resistant C1 and C3 clones had lower MITF, PGC-1α, and PRDX1 expression, while C1 had higher AXL and decreased pigmentation markers, linking PRDX1 to clonal heterogeneity and resistance. PRDX2 is depleted in acquired BRAFi-resistant cells and acts as a redox sensor. Our results illustrate that decreased pigmentation markers are related to therapy resistance and decreased antioxidant defense.

Current Landscape of Cancer Immunotherapy: Harnessing the Immune Arsenal to Overcome Immune Evasion

Cancer immune evasion represents a leading hallmark of cancer, posing a significant obstacle to the development of successful anticancer therapies. However, the landscape of cancer treatment has significantly evolved, transitioning into the era of immunotherapy from conventional methods such as surgical resection, radiotherapy, chemotherapy, and targeted drug therapy. Immunotherapy has emerged as a pivotal component in cancer treatment, harnessing the body's immune system to combat cancer and offering improved prognostic outcomes for numerous patients. The remarkable success of immunotherapy has spurred significant efforts to enhance the clinical efficacy of existing agents and strategies. Several immunotherapeutic approaches have received approval for targeted cancer treatments, while others are currently in preclinical and clinical trials. This review explores recent progress in unraveling the mechanisms of cancer immune evasion and evaluates the clinical effectiveness of diverse immunotherapy strategies, including cancer vaccines, adoptive cell therapy, and antibody-based treatments. It encompasses both established treatments and those currently under investigation, providing a comprehensive overview of efforts to combat cancer through immunological approaches. Additionally, the article emphasizes the current developments, limitations, and challenges in cancer immunotherapy. Furthermore, by integrating analyses of cancer immunotherapy resistance mechanisms and exploring combination strategies and personalized approaches, it offers valuable insights crucial for the development of novel anticancer immunotherapeutic strategies.

Patient-Derived Organoids Recapitulate Pathological Intrinsic and Phenotypic Features of Fibrous Dysplasia

Fibrous dysplasia (FD) is a rare bone disorder characterized by the replacement of normal bone with benign fibro-osseous tissue. Developments in our understanding of the pathophysiology and treatment options are impeded by the lack of suitable research models. In this study, we developed an in vitro organotypic model capable of recapitulating key intrinsic and phenotypic properties of FD. Initially, transcriptomic profiling of individual cells isolated from patient lesional tissues unveiled intralesional molecular and cellular heterogeneity. Leveraging these insights, we established patient-derived organoids (PDOs) using primary cells obtained from patient FD lesions. Evaluation of PDOs demonstrated preservation of fibrosis-associated constituent cell types and transcriptional signatures observed in FD lesions. Additionally, PDOs retained distinct constellations of genomic and metabolic alterations characteristic of FD. Histological evaluation further corroborated the fidelity of PDOs in recapitulating important phenotypic features of FD that underscore their pathophysiological relevance. Our findings represent meaningful progress in the field, as they open up the possibility for in vitro modeling of rare bone lesions in a three-dimensional context and may signify the first step towards creating a personalized platform for research and therapeutic studies.

Multifunctionality of cyclodextrin-based polymeric nanoparticulate delivery systems for chemotherapeutics, combination therapy, and theranostics

As cancer being the most difficult disease to treat, different kinds of medications and therapeutic approaches have been prominently developed by scientists. For certain families of drugs, such as immuno-therapeutics or antibody-drug conjugates, efficient delivery systems are required during administration to protect the drugs from chemical degradation or biological inactivation. Delivery systems with the ability to carry different therapeutics or diagnostic agents or both, hold promising potential to tackle the abnormalities behind cancer. In this context, this review provides updated insights on how cyclodextrin-based polymeric nanosystems have become an effective treatment approach against cancer. Cyclodextrins (CDs) are natural oligosaccharides that are famously exploited in pharmaceutical research due to their exceptional quality of entrapping water-insoluble molecules inside their hydrophobic core and providing enhanced solubility with the help of their hydrophilic exterior. Combining the properties of CDs with polymeric nanoparticles (PNPs) brings out excellent versatile and tunable profiles, thanks to the submicron-sized PNPs. By introducing the significance of CD as a delivery system, a collective discussion on different binding approaches and release mechanisms of CD-drug complexation, followed by their characterization studies has been done in this review. Further, in light of recent studies, the article majorly focuses on conveying how promoting CD to a polymeric and nanoscale elevates the multifunctional advantages against cancer that can be successfully applied in combination therapy and theranostics. Moreover, CD-based delivery systems including CALAA-01, CRLX101, and CRLX301, have demonstrated improved tumor targeting, reduced side effects, and prolonged drug release in preclinical studies and clinical trials.

From complexity to clarity: unravelling tumor heterogeneity through the lens of tumor microenvironment for innovative cancer therapy

Despite the tremendous clinical successes recorded in the landscape of cancer therapy, tumor heterogeneity remains a formidable challenge to successful cancer treatment. In recent years, the emergence of high-throughput technologies has advanced our understanding of the variables influencing tumor heterogeneity beyond intrinsic tumor characteristics. Emerging knowledge shows that drivers of tumor heterogeneity are not only intrinsic to cancer cells but can also emanate from their microenvironment, which significantly favors tumor progression and impairs therapeutic response. Although much has been explored to understand the fundamentals of the influence of innate tumor factors on cancer diversity, the roles of the tumor microenvironment (TME) are often undervalued. It is therefore imperative that a clear understanding of the interactions between the TME and other tumor intrinsic factors underlying the plastic molecular behaviors of cancers be identified to develop patient-specific treatment strategies. This review highlights the roles of the TME as an emerging factor in tumor heterogeneity. More particularly, we discuss the role of the TME in the context of tumor heterogeneity and explore the cutting-edge diagnostic and therapeutic approaches that could be used to resolve this recurring clinical conundrum. We conclude by speculating on exciting research questions that can advance our understanding of tumor heterogeneity with the goal of developing customized therapeutic solutions.

Exploring the role of interleukin 11 in cancer progression, patient survival, and therapeutic insights

BACKGROUND

The Interleukin (IL)-11 gene, which is one of the members of the cytokine family, has an oncogenic role in some cancers. The main goal of this study is to analyze IL-11 expression level in 14 prevalent cancers and highlights its role in patients' survival, drug resistance, and sensitivities. Also, an association of this gene with metastasis and inflammation pathways has been investigated.

METHODS AND RESULTS

Using the cancer genome atlas (TCGA) data, the level of IL-11 expression and its role in prognosis and survival rate were evaluated in 13 common cancers. Then, confirming the obtained in-silico outcomes, the relative expression level of this gene in colorectal cancer (CRC) samples and their adjusted tissues were assayed by the RT-qPCR method. Furthermore, to examine the association between IL-11 expression and drug resistance and sensitivity, PharmacoGX data was applied. The co-expression network was used to recognize the pathways in which IL-11 was involved. The results from the TCGA dataset indicated that the expression level of IL-11 increased significantly in 13 prevalence cancers compared to the control groups. Interestingly, this enhanced expression level is associated with a high rate of mortality in patients with bladder, stomach, colorectal, and endometrial cancers. Also, the co-expression network analysis showed a strong correlation between IL-11 and the genes of metastasis pathway and the genes related to the inflammation process. Finally, regarding drug sensitivity, IL-11 expression level can be introduced as a remarkable biomarker for cancer detection due to area under curve (AUC).

CONCLUSION

Altered expression of the IL-11 gene is observed in 13 common cancers and is associated with prognosis and mortality rate in patients. Moreover, this gene can be considered a prognostic biomarker in different types of cancer, such as CRC.

Molecular diversity in isocitrate dehydrogenase-wild-type glioblastoma

In the dynamic landscape of glioblastoma, the 2021 World Health Organization Classification of Central Nervous System tumours endeavoured to establish biological homogeneity, yet isocitrate dehydrogenase-wild-type (IDH-wt) glioblastoma persists as a tapestry of clinical and molecular diversity. Intertumoural heterogeneity in IDH-wt glioblastoma presents a formidable challenge in treatment strategies. Recent strides in genetics and molecular biology have enhanced diagnostic precision, revealing distinct subtypes and invasive patterns that influence survival in patients with IDH-wt glioblastoma. Genetic and molecular biomarkers, such as the overexpression of neurofibromin 1, phosphatase and tensin homolog and/or cyclin-dependent kinase inhibitor 2A, along with specific immune cell abundance and neurotransmitters, correlate with favourable outcomes. Conversely, increased expression of epidermal growth factor receptor tyrosine kinase, platelet-derived growth factor receptor alpha and/or vascular endothelial growth factor receptor, coupled with the prevalence of glioma stem cells, tumour-associated myeloid cells, regulatory T cells and exhausted effector cells, signifies an unfavourable prognosis. The methylation status of O6-methylguanine-DNA methyltransferase and the influence of microenvironmental factors and neurotransmitters further shape treatment responses. Understanding intertumoural heterogeneity is complemented by insights into intratumoural dynamics and cellular interactions within the tumour microenvironment. Glioma stem cells and immune cell composition significantly impact progression and outcomes, emphasizing the need for personalized therapies targeting pro-tumoural signalling pathways and resistance mechanisms. A successful glioblastoma management demands biomarker identification, combination therapies and a nuanced approach considering intratumoural variability. These advancements herald a transformative era in glioblastoma comprehension and treatment.

Multi-b-value DWI to evaluate the synergistic antiproliferation and anti-heterogeneity effects of bufalin plus sorafenib in an orthotopic HCC model

BACKGROUND

Multi-b-value diffusion-weighted imaging (DWI) with different postprocessing models allows for evaluating hepatocellular carcinoma (HCC) proliferation, spatial heterogeneity, and feasibility of treatment strategies. We assessed synergistic effects of bufalin+sorafenib in orthotopic HCC-LM3 xenograft nude mice by using intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI), a stretched exponential model (SEM), and a fractional-order calculus (FROC) model.

METHODS

Twenty-four orthotopic HCC-LM3 xenograft mice were divided into bufalin+sorafenib, bufalin, sorafenib treatment groups, and a control group. Multi-b-value DWI was performed using a 3-T scanner after 3 weeks' treatment to obtain true diffusion coefficient Dt, pseudo-diffusion coefficient Dp, perfusion fraction f, mean diffusivity (MD), mean kurtosis (MK), distributed diffusion coefficient (DDC), heterogeneity index α, diffusion coefficient D, fractional order parameter β, and microstructural quantity μ. Necrotic fraction (NF), standard deviation (SD) of hematoxylin-eosin staining, and microvessel density (MVD) of anti-CD31 staining were evaluated. Correlations of DWI parameters with histopathological results were analyzed, and measurements were compared among four groups.

RESULTS

In the final 22 mice, f positively correlated with MVD (r = 0.679, p = 0.001). Significantly good correlations of MK (r = 0.677), α (r = -0.696), and β (r= -0.639) with SD were observed (all p < 0.010). f, MK, MVD, and SD were much lower, while MD, α, β, and NF were higher in bufalin plus sorafenib group than control group (all p < 0.050).

CONCLUSION

Evaluated by IVIM, DKI, SEM, and FROC, bufalin+sorafenib was found to inhibit tumor proliferation and angiogenesis and reduce spatial heterogeneity in HCC-LM3 models.

RELEVANCE STATEMENT

Multi-b-value DWI provides potential metrics for evaluating the efficacy of treatment in HCC.

KEY POINTS

• Bufalin plus sorafenib combination may increase the effectiveness of HCC therapy. • Multi-b-value DWI depicted HCC proliferation, angiogenesis, and spatial heterogeneity. • Multi-b-value DWI may be a noninvasive method to assess HCC therapeutic efficacy.

De novo detection of somatic variants in long-read single-cell RNA sequencing data

In cancer, genetic and transcriptomic variations generate clonal heterogeneity, possibly leading to treatment resistance. Long-read single-cell RNA sequencing (LR scRNA-seq) has the potential to detect genetic and transcriptomic variations simultaneously. Here, we present LongSom, a computational workflow leveraging LR scRNA-seq data to call de novo somatic single-nucleotide variants (SNVs), copy-number alterations (CNAs), and gene fusions to reconstruct the tumor clonal heterogeneity. For SNV calling, LongSom distinguishes somatic SNVs from germline polymorphisms by reannotating marker gene expression-based cell types using called variants and applying strict filters. Applying LongSom to ovarian cancer samples, we detected clinically relevant somatic SNVs that were validated against single-cell and bulk panel DNA-seq data and could not be detected with short-read (SR) scRNA-seq. Leveraging somatic SNVs and fusions, LongSom found subclones with different predicted treatment outcomes. In summary, LongSom enables de novo SNVs, CNAs, and fusions detection, thus enabling the study of cancer evolution, clonal heterogeneity, and treatment resistance.

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.

Using imaging modalities to predict nanoparticle distribution and treatment efficacy in solid tumors: The growing role of ultrasound

Nanomedicine in oncology has not had the success in clinical impact that was anticipated in the early stages of the field's development. Ideally, nanomedicines selectively accumulate in tumor tissue and reduce systemic side effects compared to traditional chemotherapeutics. However, this has been more successful in preclinical animal models than in humans. The causes of this failure to translate may be related to the intra- and inter-patient heterogeneity of the tumor microenvironment. Predicting whether a patient will respond positively to treatment prior to its initiation, through evaluation of characteristics like nanoparticle extravasation and retention potential in the tumor, may be a way to improve nanomedicine success rate. While there are many potential strategies to accomplish this, prediction and patient stratification via noninvasive medical imaging may be the most efficient and specific strategy. There have been some preclinical and clinical advances in this area using MRI, CT, PET, and other modalities. An alternative approach that has not been studied as extensively is biomedical ultrasound, including techniques such as multiparametric contrast-enhanced ultrasound (mpCEUS), doppler, elastography, and super-resolution processing. Ultrasound is safe, inexpensive, noninvasive, and capable of imaging the entire tumor with high temporal and spatial resolution. In this work, we summarize the in vivo imaging tools that have been used to predict nanoparticle distribution and treatment efficacy in oncology. We emphasize ultrasound imaging and the recent developments in the field concerning CEUS. The successful implementation of an imaging strategy for prediction of nanoparticle accumulation in tumors could lead to increased clinical translation of nanomedicines, and subsequently, improved patient outcomes. This article is categorized under: Diagnostic Tools In Vivo Nanodiagnostics and Imaging Therapeutic Approaches and Drug Discovery Nanomedicine for Oncologic Disease Therapeutic Approaches and Drug Discovery Emerging Technologies.

Combination Chemotherapy Optimization with Discrete Dosing

Chemotherapy drug administration is a complex problem that often requires expensive clinical trials to evaluate potential regimens; one way to alleviate this burden and better inform future trials is to build reliable models for drug administration. This paper presents a mixed-integer program for combination chemotherapy (utilization of multiple drugs) optimization that incorporates various important operational constraints and, besides dose and concentration limits, controls treatment toxicity based on its effect on the count of white blood cells. To address the uncertainty of tumor heterogeneity, we also propose chance constraints that guarantee reaching an operable tumor size with a high probability in a neoadjuvant setting. We present analytical results pertinent to the accuracy of the model in representing biological processes of chemotherapy and establish its potential for clinical applications through a numerical study of breast cancer.

Rationally designed approaches to augment CAR-T therapy for solid tumor treatment

Chimeric antigen receptor T cell denoted as CAR-T therapy has realized incredible therapeutic advancements for B cell malignancy treatment. However, its therapeutic validity has yet to be successfully achieved in solid tumors. Different from hematological cancers, solid tumors are characterized by dysregulated blood vessels, dense extracellular matrix, and filled with immunosuppressive signals, which together result in CAR-T cells' insufficient infiltration and rapid dysfunction. The insufficient recognition of tumor cells and tumor heterogeneity eventually causes cancer reoccurrences. In addition, CAR-T therapy also raises safety concerns, including potential cytokine release storm, on-target/off-tumor toxicities, and neuro-system side effects. Here we comprehensively review various targeting aspects, including CAR-T cell design, tumor modulation, and delivery strategy. We believe it is essential to rationally design a combinatory CAR-T therapy via constructing optimized CAR-T cells, directly manipulating tumor tissue microenvironments, and selecting the most suitable delivery strategy to achieve the optimal outcome in both safety and efficacy.

Deciphering cellular plasticity in pancreatic cancer for effective treatments

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

Current Role and Future Prospects of Positron Emission Tomography (PET)/Computed Tomography (CT) in the Management of Breast Cancer

Breast cancer has become the most diagnosed cancer in women globally, with 2.3 million new diagnoses each year. Accurate early staging is essential for improving survival rates with metastatic spread from loco regional to distant metastasis, decreasing mortality rates by 50%. Current guidelines do not advice the routine use of positron emission tomography (PET)-computed tomography (CT) in the staging of early breast cancer in the absence of symptoms. However, there is a growing body of evidence to suggest that the use of PET-CT in this early stage can benefit the patient by improving staging and as a result treatment and outcomes, as well as psychological burden, without increasing costs to the health service. Ongoing research in PET radiomics and artificial intelligence is showing promising future prospects in its use in diagnosis, staging, prognostication, and assessment of responses to the treatment of breast cancer. Furthermore, ongoing research to address current limitations of PET-CT by improving techniques and tracers is encouraging. In this narrative review, we aim to evaluate the current evidence of the usefulness of PET-CT in the management of breast cancer in different settings along with its future prospects, including the use of artificial intelligence (AI), radiomics, and novel tracers.

Neurotrophic-tyrosine receptor kinase gene fusion in papillary thyroid cancer: A clinicogenomic biobank and record linkage study from Finland

Selective tropomyosin receptor kinase (TRK) inhibitors are approved targeted therapies for patients with solid tumors harboring a neurotrophic tyrosine receptor kinase (NTRK) gene fusion. Country-specific estimates of NTRK gene fusion frequency, and knowledge on the characteristics of affected patients, are limited. We identified patients with histologically-confirmed papillary thyroid cancer (PTC) from Finland's Auria Biobank. TRK protein expression was determined by pan-TRK immunohistochemistry. Immuno-stained tumor samples were scored by a certified pathologist. Gene fusions and other co-occurring gene alterations were identified by next generation sequencing. Patient characteristics and vital status were determined from linked hospital electronic health records (EHRs). Patients were followed from 1 year before PTC diagnosis until death. 6/389 (1.5%) PTC patients had an NTRK gene fusion (all NTRK3); mean age 43.8 years (and none had comorbidities) at PTC diagnosis. Gene fusion partners were EML4 (n = 3), ETV6 (n = 2), and RBPMS (n = 1). Of 3/6 patients with complete EHRs, all received radioactive iodine ablation only and were alive at end of follow-up (median observation, 9.12 years). In conclusion, NTRK gene fusion is infrequent in patients with PTC. Linkage of biobank samples to EHRs is feasible in describing the characteristics and outcomes of patients with PTC and potentially other cancer types.

Advancements in Preclinical Models of Pancreatic Cancer

ABSTRACT

Pancreatic cancer remains one of the deadliest of all cancer types with a 5-year overall survival rate of just 12%. Preclinical models available for understanding the disease pathophysiology have evolved significantly in recent years. Traditionally, commercially available 2-dimensional cell lines were developed to investigate mechanisms underlying tumorigenesis, metastasis, and drug resistance. However, these cells grow as monolayer cultures that lack heterogeneity and do not effectively represent tumor biology. Developing patient-derived xenografts and genetically engineered mouse models led to increased cellular heterogeneity, molecular diversity, and tissues that histologically represent the original patient tumors. However, these models are relatively expensive and very timing consuming. More recently, the advancement of fast and inexpensive in vitro models that better mimic disease conditions in vivo are on the rise. Three-dimensional cultures like organoids and spheroids have gained popularity and are considered to recapitulate complex disease characteristics. In addition, computational genomics, transcriptomics, and metabolomic models are being developed to simulate pancreatic cancer progression and predict better treatment strategies. Herein, we review the challenges associated with pancreatic cancer research and available analytical models. We suggest that an integrated approach toward using these models may allow for developing new strategies for pancreatic cancer precision medicine.

Clinical and Genetic Characteristics of Early and Advanced Gastric Cancer

Gastric cancer (GC) persists as the fourth most prevalent cause of global cancer-related mortality, presenting a challenge due to the scarcity of available therapeutic strategies. Precision medicine is crucial not only in the treatment but also in the management of GC. We performed gene panel sequencing with Oncomine focus assay comprising 52 cancer-associated genes and MSI analysis in 100 case-matched gastric cancer cases. A comprehensive analysis of clinical and genetic characteristics was conducted on these genetic results and clinicopathological findings. Upon comparison of clinicopathological characteristics, significant differences between early gastric cancer (EGC) and advanced gastric cancer (AGC) were observed in tumor location (p = 0.003), Lauren classification (p = 0.015), T stage (p = 0.000), and N stage (p = 0.015). The six most frequently mutated genes were PIK3CA (29%, 10/35), ERBB2 (17%, 6/35), KRAS (14%, 5/35), ALK (6%, 2/35), ESR1 (6%, 2/35), and FGFR3 (6%, 2/35). Regarding genetic variation, there was a tendency for the N stage to be higher in GC patients with mutated genes (p = 0.014). The frequency of mutations in GC patients was statistically significantly higher in AGC (n = 24) compared to EGC (n = 11) (odds ratio, 2.792; 95% confidence interval, 1.113 to 7.007; p = 0.026). Six of the ten GC patients carrying mutated genes and exhibiting MSI were classified into intestinal-type and undifferentiated GC, with the location of the tumor being in the lower-third. Among these patients, five harbored mutated PIK3CA, while the remaining patient had a mutation in ALK. Conclusions: AGC patients more frequently exhibited alterations of PIK3CA, KRAS, and ERBB2 as somatic oncogenic drivers, and displayed a higher prevalence of cumulative genetic events, including increased rates of PIK3CA mutations, enhanced detection of immunotherapy biomarkers, and mutations of the ESR1 gene.

P53 loss of heterozygosity (LOH) in formalin-fixed paraffin-embedded leiomyosarcoma (LMS): a novel report

BACKGROUND

The occurrence of p53 loss of heterozygosity (LOH) is a common genetic event in malignancy. LOH occurs when a heterozygous locus loses one of its two parental alleles, becoming homozygous at that locus, by either copy number loss (CNL-LOH) or by becoming copy number neutral (CNN-LOH). A role for CNL-LOH (cnLOH) has been postulated in cancer aetiology. Loss of heterozygosity (LOH) results in irreversible genetic loss.

AIMS

LOH was determined in DNA extracted from formalin-fixed paraffin-embedded (FFPE) leiomyosarcoma (LMS) specimens in a retrospective study from 30 patients, to assess the prognostic significance of LOH. The findings were analysed and their validity assessed. LOH was an adverse prognostic factor in LMS. Prospective uniform standardisation of formalin-fixation techniques is required.

METHODS

DNA was extracted from 169 formalin-fixed paraffin blocks of 30 patients with LMS, following extensive tissue microdissection. Genomic DNA was amplified using the polymerase chain reaction (PCR) technique. Fluorescence-based microsatellite PCR was used to detect and quantitate heterozygosity loss.

RESULTS

LOH was detected at gene locus 17p13 in 16 LMS (Four grade 2 and 12 grade 3 LMS). LOH was not detected in 14 LMS cases (one grade 1, five grade 2 and eight grade 3 LMS). LOH was associated with shorter patient survival.

CONCLUSIONS

The results reported herein endorse the value of utilizing FFPE DNA in identifying LOH as a prognostic factor in LMS. The results have implications for tumour biobanking and precision medicine in patients with sarcomas.

E2F1 mediates competition, proliferation and response to cisplatin in cohabitating resistant and sensitive ovarian cancer cells

Background

Tumor heterogeneity is one of the key factors leading to chemo-resistance relapse. It remains unknown how resistant cancer cells influence sensitive cells during cohabitation and growth within a heterogenous tumors. The goal of our study was to identify driving factors that mediate the interactions between resistant and sensitive cancer cells and to determine the effects of cohabitation on both phenotypes.

Methods

We used isogenic ovarian cancer (OC) cell lines pairs, sensitive and resistant to platinum: OVCAR5 vs. OVCAR5 CisR and PE01 vs. PE04, respectively, to perform long term direct culture and to study the phenotypical changes of the interaction of these cells.

Results

Long term direct co-culture of sensitive and resistant OC cells promoted proliferation (p < 0.001) of sensitive cells and increased the proportion of cells in the G1 and S cell cycle phase in both PE01 and OVCAR5 cells. Direct co-culture led to a decrease in the IC50 to platinum in the cisplatin-sensitive cells (5.92 µM to 2.79 µM for PE01, and from 2.05 µM to 1.51 µM for OVCAR5). RNAseq analysis of co-cultured cells showed enrichment of Cell Cycle Control, Cyclins and Cell Cycle Regulation pathways. The transcription factor E2F1 was predicted as the main effector responsible for the transcriptomic changes in sensitive cells. Western blot and qRT-PCR confirmed upregulation of E2F1 in co-cultured vs monoculture. Furthermore, an E2F1 inhibitor reverted the increase in proliferation rate induced by co-culture to baseline levels.

Conclusion

Our data suggest that long term cohabitation of chemo-sensitive and -resistant cancer cells drive sensitive cells to a higher proliferative state, more responsive to platinum. Our results reveal an unexpected effect caused by direct interactions between cancer cells with different proliferative rates and levels of platinum resistance, modelling competition between cells in heterogeneous tumors.

A new era in cancer treatment: harnessing ZIF-8 nanoparticles for PD-1 inhibitor delivery

This review delves into the potential of zeolitic imidazolate framework-8 (ZIF-8) nanoparticles in augmenting the efficacy of cancer immunotherapy, with a special focus on the delivery of programmed cell death receptor 1 (PD-1) inhibitors. The multifunctional nature of ZIF-8 nanoparticles as drug carriers is emphasized, with their ability to encapsulate a range of therapeutic agents, including PD-1 inhibitors, and facilitate their targeted delivery to tumor locations. By manipulating the pore size and surface characteristics of ZIF-8 nanoparticles, controlled drug release can be realized. The strategic use of ZIF-8 nanoparticles to deliver PD-1 inhibitors presents a precise and targeted modality for cancer treatment, reducing off-target impacts and enhancing therapeutic effectiveness. This combined strategy addresses the existing challenges and constraints of current immunotherapy techniques, with the ultimate goal of enhancing patient outcomes in cancer therapy.

Novel LIPA-Targeted Therapy for Treating Ovarian Cancer

Ovarian cancer (OCa) is the most lethal form of gynecologic cancer, and the tumor heterogeneities at the molecular, cellular, and tissue levels fuel tumor resistance to standard therapies and pose a substantial clinical challenge. Here, we tested the hypothesis that the heightened basal endoplasmic reticulum stress (ERS) observed in OCa represents an exploitable vulnerability and may overcome tumor heterogeneity. Our recent studies identified LIPA as a novel target to induce ERS in cancer cells using the small molecule ERX-41. However, the role of LIPA and theutility of ERX-41 to treat OCa remain unknown. Expression analysis using the TNMplot web tool, TCGA data sets, and immunohistochemistry analysis using a tumor tissue array showed that LIPA is highly expressed in OCa tissues, compared to normal tissues. ERX-41 treatment significantly reduced the cell viability and colony formation ability and promoted the apoptosis of OCa cells. Mechanistic studies revealed a robust and consistent induction of ERS markers, including CHOP, elF2α, PERK, and ATF4, upon ERX-41 treatment. In xenograft and PDX studies, ERX-41 treatment resulted in a significant reduction in tumor growth. Collectively, our results suggest that ERX-41 is a novel therapeutic agent that targets the LIPA with a unique mechanism of ERS induction, which could be exploited to treat heterogeneity in OCa.

Pattern recognition of microcirculation with super-resolution ultrasound imaging provides markers for early tumor response to anti-angiogenic therapy

Rationale: Cancer treatment outcome is traditionally evaluated by tumor volume change in clinics, while tumor microvascular heterogeneity reflecting tumor response has not been fully explored due to technical limitations. Methods: We introduce a new paradigm in super-resolution ultrasound imaging, termed pattern recognition of microcirculation (PARM), which identifies both hemodynamic and morphological patterns of tumor microcirculation hidden in spatio-temporal space trajectories of microbubbles. Results: PARM demonstrates the ability to distinguish different local blood flow velocities separated by a distance of 24 μm. Compared with traditional vascular parameters, PARM-derived heterogeneity parameters prove to be more sensitive to microvascular changes following anti-angiogenic therapy. Particularly, PARM-identified "sentinel" microvasculature, exhibiting evident structural changes as early as 24 hours after treatment initiation, correlates significantly with subsequent tumor volume changes (|r| > 0.9, P < 0.05). This provides prognostic insight into tumor response much earlier than clinical criteria. Conclusions: The ability of PARM to noninvasively quantify tumor vascular heterogeneity at the microvascular level may shed new light on early-stage assessment of cancer therapy.

Biophysical Control of the Glioblastoma Immunosuppressive Microenvironment: Opportunities for Immunotherapy

GBM is the most aggressive and common form of primary brain cancer with a dismal prognosis. Current GBM treatments have not improved patient survival, due to the propensity for tumor cell adaptation and immune evasion, leading to a persistent progression of the disease. In recent years, the tumor microenvironment (TME) has been identified as a critical regulator of these pro-tumorigenic changes, providing a complex array of biomolecular and biophysical signals that facilitate evasion strategies by modulating tumor cells, stromal cells, and immune populations. Efforts to unravel these complex TME interactions are necessary to improve GBM therapy. Immunotherapy is a promising treatment strategy that utilizes a patient's own immune system for tumor eradication and has exhibited exciting results in many cancer types; however, the highly immunosuppressive interactions between the immune cell populations and the GBM TME continue to present challenges. In order to elucidate these interactions, novel bioengineering models are being employed to decipher the mechanisms of immunologically "cold" GBMs. Additionally, these data are being leveraged to develop cell engineering strategies to bolster immunotherapy efficacy. This review presents an in-depth analysis of the biophysical interactions of the GBM TME and immune cell populations as well as the systems used to elucidate the underlying immunosuppressive mechanisms for improving current therapies.