Role of intratumoural heterogeneity in cancer drug resistance: molecular and clinical perspectives

Drug response-based precision therapeutic selection for tamoxifen-resistant triple-positive breast cancer

Breast cancer adaptability to the drug environment reduces the chemotherapeutic response and facilitates acquired drug resistance. Cancer-specific therapeutics can be more effective against advanced-stage cancer than standard chemotherapeutics. To extend the paradigm of cancer-specific therapeutics, clinically relevant acquired tamoxifen-resistant MCF-7 proteome was deconstructed to identify possible druggable targets (N = 150). Twenty-eight drug inhibitors were used against identified druggable targets to suppress non-resistant (NC) and resistant cells (RC). First, selected drugs were screened using growth-inhibitory response against NC and RC. Seven drugs were shortlisted for their time-dependent (10-12 days) cytotoxic effect and further narrowed to three effective drugs (e.g., cisplatin, doxorubicin, and hydroxychloroquine). The growth-suppressive effectiveness of selected drugs was validated in the complex spheroid model (progressive and regressive). In the progressive model, doxorubicin (RC: 83.64 %, NC: 54.81 %), followed by cisplatin (RC: 76.66 %, NC: 68.94 %) and hydroxychloroquine (RC: 68.70 %, NC: 61.78 %) showed a significant growth-suppressive effect. However, in fully grown regressive spheroid, after 4th drug treatment, cisplatin significantly suppressed RC (84.79 %) and NC (40.21 %), while doxorubicin and hydroxychloroquine significantly suppressed only RC (76.09 and 76.34 %). Our in-depth investigation effectively integrated the expression data with the cancer-specific therapeutic investigation. Furthermore, our three-step sequential drug-screening approach unbiasedly identified cisplatin, doxorubicin, and hydroxychloroquine as an efficacious drug to target heterogeneous cancer cell populations. SIGNIFICANCE STATEMENT: Hormonal-positive BC grows slowly, and hormonal-inhibitors effectively suppress the oncogenesis. However, development of drug-resistance not only reduces the drug-response but also increases the chance of BC aggressiveness. Further, alternative chemotherapeutics are widely used to control advanced-stage BC. In contrast, we hypothesized that, compared to standard chemotherapeutics, cancer-specific drugs can be more effective against resistant-cancer. Although cancer-specific treatment identification is an uphill battle, our work shows proteome data can be used for drug selection. We identified multiple druggable targets and, using ex-vivo methods narrowed multiple drugs to disease-condition-specific therapeutics. We consider that our investigation successfully interconnected the expression data with the functional disease-specific therapeutic investigation and selected drugs can be used for effective resistant treatment with higher therapeutic response.

Investigating druggable kinases for targeted therapy in retinoblastoma

Retinoblastoma (RB) is a childhood retinal neoplasm and commonly treated with cytotoxic chemotherapeutic agents. However, these therapeutic approaches often lead to diverse adverse effects. A precise molecular therapy will alleviate these side effects and offer better treatment outcomes. Over the years, kinases have become potential drug targets in cancer therapy. Hence, we aimed to investigate genetic alterations of putative kinase drug targets in RB. Targeted exome sequencing was performed on 35 RB tumors with paired blood samples using a gene panel consisting of 29 FDA-approved kinase genes. Single nucleotide variants were analyzed for pathogenicity using an in-house pipeline and copy number variations (CNVs) were detected by a depth of coverage and CNVPanelizer. The correlation between genetic changes and clinicopathological features was assessed using GraphPad Prism. Three somatic mutations, two in ERBB4 and one in EGFR were identified. Two of these mutations (ERBB4 c.C3836A & EGFR c.A1196T) were not reported earlier. CNV analysis revealed recurrent gains of ALK, MAP2K2, SRC, STK11, and FGFR3 as well as frequent losses of ATM, PI3KCA and ERBB4. Notably, nonresponsive tumors had a higher incidence of amplifications in clinically actionable genes such as ALK. Moreover, ALK gain and ATM loss were strongly correlated with optic nerve head invasion. In conclusion, our study revealed genetic alterations of druggable kinases in RB, providing preliminary insights for the exploration of kinase-targeted therapy in RB.

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.

Advancing immunotherapy for melanoma: the critical role of single-cell analysis in identifying predictive biomarkers

Melanoma, a malignant skin cancer arising from melanocytes, exhibits rapid metastasis and a high mortality rate, especially in advanced stages. Current treatment modalities, including surgery, radiation, and immunotherapy, offer limited success, with immunotherapy using immune checkpoint inhibitors (ICIs) being the most promising. However, the high mortality rate underscores the urgent need for robust, non-invasive biomarkers to predict patient response to adjuvant therapies. The immune microenvironment of melanoma comprises various immune cells, which influence tumor growth and immune response. Melanoma cells employ multiple mechanisms for immune escape, including defects in immune recognition and epithelial-mesenchymal transition (EMT), which collectively impact treatment efficacy. Single-cell analysis technologies, such as single-cell RNA sequencing (scRNA-seq), have revolutionized the understanding of tumor heterogeneity and immune microenvironment dynamics. These technologies facilitate the identification of rare cell populations, co-expression patterns, and regulatory networks, offering deep insights into tumor progression, immune response, and therapy resistance. In the realm of biomarker discovery for melanoma, single-cell analysis has demonstrated significant potential. It aids in uncovering cellular composition, gene profiles, and novel markers, thus advancing diagnosis, treatment, and prognosis. Additionally, tumor-associated antibodies and specific genetic and cellular markers identified through single-cell analysis hold promise as predictive biomarkers. Despite these advancements, challenges such as RNA-protein expression discrepancies and tumor heterogeneity persist, necessitating further research. Nonetheless, single-cell analysis remains a powerful tool in elucidating the mechanisms underlying therapy response and resistance, ultimately contributing to the development of personalized melanoma therapies and improved patient outcomes.

PCK1 attenuates tumor stemness via activating the Hippo signaling pathway in hepatocellular carcinoma

Liver cancer stem cells were found to rely on glycolysis as the preferred metabolic program. Phosphoenolpyruvate carboxylase 1 (PCK1), a gluconeogenic metabolic enzyme, is down-regulated in hepatocellular carcinoma and is closely related to poor prognosis. The oncogenesis and progression of tumors are closely related to cancer stem cells. It is not completely clear whether the PCK1 deficiency increases the stemness of hepatoma cells and promotes the oncogenesis of hepatocellular carcinoma. Herein, the results showed that PCK1 inhibited the self-renewal property of hepatoma cells, reduced the mRNA level of cancer stem cell markers, and inhibited tumorigenesis. Moreover, PCK1 increased the sensitivity of hepatocellular carcinoma cells to sorafenib. Furthermore, we found that PCK1 activated the Hippo pathway by enhancing the phosphorylation of YAP and inhibiting its nuclear translocation. Verteporfin reduced the stemness of hepatoma cells and promoted the pro-apoptotic effect of sorafenib. Thus, combined treatment with verteporfin and sorafenib may be a potential anti-tumor strategy in hepatocellular carcinoma.

Multidimensional analysis of TMEM132A in pan-cancer: unveiling its potential as a biomarker for treatment response prediction

Background: TMEM132A is a transmembrane protein that regulates gastric cancer cell malignancy and overall survival in bladder cancer patients. However, while some studies have investigated the involvement of TMEM132A in specific cancers, further systematic studies are required to elucidate its specific mechanisms of action in different cancer types. Methods: We investigated the pan-cancer role of TMEM132A using several databases. We analyzed TMEM132A expression and its correlation with clinical survival, immune checkpoints, tumor stemness score, prognostic value, immunomodulators, genomic profiles, immunological characteristics, immunotherapy and functional enrichment. Results: First, it was observed that TMEM132A expression levels were higher in the majority of tumors compared to non-tumor tissues. In addition, high TMEM132A expression may have a higher prognostic value in some cancers. Furthermore, TMEM132A was significantly associated with immune checkpoints, immunomodulators, prognosis, immunomodulatory genes, tumor stemness score, cell function status and immune infiltration in most tumors. Further analysis of TMEM132A-related gene enrichment, mutation sites and types, RNA modification and genomic heterogeneity showed that the major mutations of TMEM132A were missense mutations and that TMEM132A plays a very important role in UCEC, LUAD and LIHC. Finally, these results suggest that high TMEM132A expression may be associated with a better response to specific immunotherapies. Conclusion: This comprehensive study uncovers an important function for TMEM132A in different types of cancer. It also has the potential to identify TMEM132A as a potential biomarker for predicting treatment response. This may help us to better understand how TMEM132A plays a role in cancer and provide valuable insights for developing personalised treatments.

Whole-tumoral metabolic heterogeneity in 18F-FDG PET/CT is a novel prognostic marker for neuroblastoma

BACKGROUND

Neuroblastoma (NB) is a highly heterogeneous tumor, and more than half of newly diagnosed NB are associated with extensive metastases. Accurately characterizing the heterogeneity of whole-body tumor lesions remains clinical challenge. This study aims to quantify whole-tumoral metabolic heterogeneity (WMH) derived from whole-body tumor lesions, and investigate the prognostic value of WMH in NB.

METHODS

We retrospectively enrolled 95 newly diagnosed pediatric NB patients in our department. Traditional semi-quantitative PET/CT parameters including the maximum standardized uptake value (SUVmax), the mean standardized uptake value (SUVmean), the peak standardized uptake value (SUVpeak), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were measured. These PET/CT parameters were expressed as PSUVmax, PSUVmean, PSUVpeak, PMTV, PTLG for primary tumor, WSUVmax, WSUVmean, WSUVpeak, WMTV, WTLG for whole-body tumor lesions. The metabolic heterogeneity was quantified using the areas under the curve of the cumulative SUV-volume histogram index (AUC-CSH index). Intra-tumoral metabolic heterogeneity (IMH) and WMH were extracted from primary tumor and whole-body tumor lesions, respectively. The outcome endpoints were overall survival (OS) and progression-free survival (PFS). Survival analysis was performed utilizing the univariate and multivariate Cox proportional hazards regression. The optimal cut-off values for metabolic parameters were obtained by receiver operating characteristic curve (ROC).

RESULTS

During follow up, 27 (28.4%) patients died, 21 (22.1%) patients relapsed and 47 (49.5%) patients remained progression-free survival, with a median follow-up of 35.0 months. In survival analysis, WMTV and WTLG were independent indicators of PFS, and WMH was an independent risk factor of PFS and OS. However, IMH only showed association with PFS and OS. In addition to metabolic parameters, the International Neuroblastoma Staging System (INSS) was identified as an independent risk factor for PFS, and neuron-specific enolase (NSE) served as an independent predictor of OS.

CONCLUSION

WMH was an independent risk factor for PFS and OS, suggesting its potential as a novel prognostic marker for newly diagnosed NB patients.

Current status and advances to improving drug delivery in diffuse intrinsic pontine glioma

Diffuse midline glioma (DMG), including tumors diagnosed in the brainstem (diffuse intrinsic pontine glioma - DIPG), is the primary cause of brain tumor-related death in pediatric patients. DIPG is characterized by a median survival of <12 months from diagnosis, harboring the worst 5-year survival rate of any cancer. Corticosteroids and radiation are the mainstay of therapy; however, they only provide transient relief from the devastating neurological symptoms. Numerous therapies have been investigated for DIPG, but the majority have been unsuccessful in demonstrating a survival benefit beyond radiation alone. Although many barriers hinder brain drug delivery in DIPG, one of the most significant challenges is the blood-brain barrier (BBB). Therapeutic compounds must possess specific properties to enable efficient passage across the BBB. In brain cancer, the BBB is referred to as the blood-brain tumor barrier (BBTB), where tumors disrupt the structure and function of the BBB, which may provide opportunities for drug delivery. However, the biological characteristics of the brainstem's BBB/BBTB, both under normal physiological conditions and in response to DIPG, are poorly understood, which further complicates treatment. Better characterization of the changes that occur in the BBB/BBTB of DIPG patients is essential, as this informs future treatment strategies. Many novel drug delivery technologies have been investigated to bypass or disrupt the BBB/BBTB, including convection enhanced delivery, focused ultrasound, nanoparticle-mediated delivery, and intranasal delivery, all of which are yet to be clinically established for the treatment of DIPG. Herein, we review what is known about the BBB/BBTB and discuss the current status, limitations, and advances of conventional and novel treatments to improving brain drug delivery in DIPG.

Mechanisms of Sorafenib Resistance in HCC Culture Relate to the Impaired Membrane Expression of Organic Cation Transporter 1 (OCT1)

Introduction

Sorafenib, an FDA-approved drug for advanced hepatocellular carcinoma (HCC) treatment, encounters resistance in many patients. Deciphering the mechanisms underlying sorafenib resistance is crucial for devising alternative strategies to overcome it.

Aim

This study aimed to investigate sorafenib resistance mechanisms using a diverse panel of HCC cell lines.

Methods

HCC cell lines were subjected to continuous sorafenib treatment, and stable cell lines (Huh 7.5 and Huh 7PX) exhibiting sustained growth in its presence were isolated. The investigation of drug resistance mechanisms involved a comparative analysis of drug-targeted signal transduction pathways (EGFR/RAF/MEK/ERK/Cyclin D), sorafenib uptake, and membrane expression of the drug uptake transporter.

Results

HCC cell lines (Huh 7.5 and Huh 7PX) with a higher IC50 (10μM) displayed a more frequent development of sorafenib resistance compared to those with a lower IC50 (2-4.8μM), indicating a potential impact of IC50 variation on initial treatment response. Our findings reveal that activated overexpression of Raf1 kinases and impaired sorafenib uptake, mediated by reduced membrane expression of organic cation transporter-1 (OCT1), contribute to sorafenib resistance in HCC cultures. Stable expression of the drug transporter OCT1 through cDNA transfection or adenoviral delivery of OCT1 mRNA increased sorafenib uptake and successfully overcame sorafenib resistance. Additionally, consistent with sorafenib resistance in HCC cultures, cirrhotic liver-associated human HCC tumors often exhibited impaired membrane expression of OCT1 and OCT3.

Conclusion

Intrinsic differences among HCC cell clones, affecting sorafenib sensitivity at the expression level of Raf kinases, drug uptake, and OCT1 transporters, were identified. This study underscores the potential of HCC tumor targeted OCT1 expression to enhance sorafenib treatment response.

Predictive value of immediate early response 5 like (IER5L) in the prognosis and immune checkpoint blockade therapy of non-small cell lung cancer patients

BACKGROUND

Non-small cell lung cancer (NSCLC) is a malignancy with high mortality. Immediate early response 5 like (IER5L) has been found to associate with worse prognosis in colorectal cancer patients. However, its role in the prognosis prediction of NSCLC has remained largely unknown.

METHODS

The IER5L expression in NSCLC and normal tissues was analyzed in two public cohorts: TCGA-LUAD-LUSC and GSE159857. Additionally, functional enrichment, survival analysis, CIBERSORT and tumor mutation burden (TMB) were investigated between low- and high-IER5L level groups. The in vitro IER5L mRNA and protein levels were determined using RT-qPCR and western blot, respectively.

RESULTS

The data from TCGA-LUAD-LUSC and GSE159857 cohorts showed a high IER5L mRNA expression in NSCLC tissue samples compared to normal controls. The increased expression of IER5L in NSCLC cells were also validated by RT-qPCR and western blot analysis. Additionally, NSCLC patients with high-IER5L level had significantly worse prognosis and IER5L could be used as an independent prognostic factor for NSCLC patients. Meanwhile, patients in the high-IER5L group had higher TMB level. IER5L expression was negatively correlated with the proportion of Monocytes and T cells CD4 memory resting, and was positively related to the proportion of Tregs and M0 macrophages in tumor tissues. Besides, transcription factors TFAP4 and ZNF692 may bind to the promoter region of IER5L, and then modulate IER5L gene transcription, thereby affecting IER5L gene expression. Furthermore, GSEA results showed that IER5L gene was closely related to MAPK, PI3K-Akt, NF-kappaB signaling pathways in NSCLC.

CONCLUSION

Collectively, high IER5L expression may be a promising unfavorable prognostic biomarker and therapeutic target for NSCLC patients.

Pharmacokinetics and apparent Michaelis constant for metabolite conversion of sorafenib in healthy and hepatocellular carcinoma-bearing rats

Aim: Investigation of the pharmacokinetics of sorafenib (SRF) in rats with hepatocellular carcinoma (HCC). Methods: A reproducible ultra-HPLC-MS method for simultaneous determination of serum SRF, N-hydroxymethyl sorafenib and N-demethylation sorafenib. Results: Both the maximum serum concentrations (2.5-times) and the area under the serum concentration-time curve from 0 h to infinity (4.5-times) of SRF were observed to be significantly higher, with a greater than 3.0-fold decrease in the clearance rate in the HCC-bearing rats compared with these values in healthy animals. Further study revealed approximately 3.8- and 3.2-times increases in the apparent Michaelis constant for N-hydroxymethyl sorafenib and N-demethylation sorafenib conversions in the HCC-bearing rats. Conclusion: The low efficiency for the SRF conversions was a key contributor to the increased serum concentrations of SRF.

Mathematical modeling of combined therapies for treating tumor drug resistance

Drug resistance is one of the most intractable issues to the targeted therapy for cancer diseases. To explore effective combination therapy schemes, we propose a mathematical model to study the effects of different treatment schemes on the dynamics of cancer cells. Then we characterize the dynamical behavior of the model by finding the equilibrium points and exploring their local stability. Lyapunov functions are constructed to investigate the global asymptotic stability of the model equilibria. Numerical simulations are carried out to verify the stability of equilibria and treatment outcomes using a set of collected model parameters and experimental data on murine colon carcinoma. Simulation results suggest that immunotherapy combined with chemotherapy contributes significantly to the control of tumor growth compared to monotherapy. Sensitivity analysis is performed to identify the importance of model parameters on the variations of model outcomes.

On minimising tumoural growth under treatment resistance

Drug resistance is a major challenge for curative cancer treatment, representing the main reason of death in patients. Evolutionary biology suggests pauses between treatment rounds as a way to delay or even avoid resistance emergence. Indeed, this approach has already shown promising preclinical and early clinical results, and stimulated the development of mathematical models for finding optimal treatment protocols. Due to their complexity, however, these models do not lend themself to a rigorous mathematical analysis, hence so far clinical recommendations generally relied on numerical simulations and ad-hoc heuristics. Here, we derive two mathematical models describing tumour growth under genetic and epigenetic treatment resistance, respectively, which are simple enough for a complete analytical investigation. First, we find key differences in response to treatment protocols between the two modes of resistance. Second, we identify the optimal treatment protocol which leads to the largest possible tumour shrinkage rate. Third, we fit the "epigenetic model" to previously published xenograft experiment data, finding excellent agreement, underscoring the biological validity of our approach. Finally, we use the fitted model to calculate the optimal treatment protocol for this specific experiment, which we demonstrate to cause curative treatment, making it superior to previous approaches which generally aimed at stabilising tumour burden. Overall, our approach underscores the usefulness of simple mathematical models and their analytical examination, and we anticipate our findings to guide future preclinical and, ultimately, clinical research in optimising treatment regimes.

Measuring Drug Response with Single-Cell Growth Rate Quantification

Intratumoral heterogeneity is a substantial cause of drug resistance development during chemotherapy or other drug treatments for cancer. Therefore, monitoring and measuring cell exposure and response to drugs at the single-cell level are crucial. Previous research suggested that the single-cell growth rate can be used to investigate drug-cell interactions. However, currently established methods for quantifying single-cell growth are limited to isolated or monolayer cells. Here, we introduce a technique that accurately measures both 2D and 3D cell growth rates using label-free ratiometric stimulated Raman scattering (SRS) microscopy. We use deuterated amino acids, leucine, isoleucine, and valine, as tracers and measure the C-D SRS signal from deuterium-labeled proteins and the C-H SRS signal from unlabeled proteins simultaneously to determine the cell growth rate at the single-cell level. The technique offers single-cell level drug sensitivity measurement with a shorter turnaround time (within 12 h) than most traditional assays. The submicrometer resolution of the imaging technique allows us to examine the effects of chemotherapeutic drugs, including kinase inhibitors, mitotic inhibitors, and topoisomerase II inhibitors, on both the cell growth rate and morphology. The capability of quantifying 3D cell growth rates provides insight into a deeper understanding of the cell-drug interaction in the actual tumor environment.

Deep-learning-assisted Sort-Seq enables high-throughput profiling of gene expression characteristics with high precision

Owing to the nondeterministic and nonlinear nature of gene expression, the steady-state intracellular protein abundance of a clonal population forms a distribution. The characteristics of this distribution, including expression strength and noise, are closely related to cellular behavior. However, quantitative description of these characteristics has so far relied on arrayed methods, which are time-consuming and labor-intensive. To address this issue, we propose a deep-learning-assisted Sort-Seq approach (dSort-Seq) in this work, enabling high-throughput profiling of expression properties with high precision. We demonstrated the validity of dSort-Seq for large-scale assaying of the dose-response relationships of biosensors. In addition, we comprehensively investigated the contribution of transcription and translation to noise production in Escherichia coli, from which we found that the expression noise is strongly coupled with the mean expression level. We also found that the transcriptional interference caused by overlapping RpoD-binding sites contributes to noise production, which suggested the existence of a simple and feasible noise control strategy in E. coli.

Nerve Growth Factor, Antimicrobial Peptides and Chemotherapy: Glioblastoma Combination Therapy to Improve Their Efficacy

Glioblastoma (GBM) is an aggressive and lethal malignancy of the central nervous system with a median survival rate of 15 months. We investigated the combined anticancer effects of nerve growth factor (NGF), cathelicidin (LL-37), and protegrin-1 (PG-1) with chemotherapy (temozolomide, doxorubicin, carboplatin, cisplatin, and etoposide) in the glioblastoma U251 cell line to overcome the limitations of conventional chemotherapy and to guarantee specific treatments to succeed. The MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay was used to study cell viability and to determine the cytotoxic effects of NGF, LL-37, and PG-1 and their combination with chemotherapy in U251 cells. Synergism or antagonism was determined using the combination index (CI) method. Caspase-3 activity was evaluated spectrophotometrically using a caspase-3 activity assay kit. Apoptosis was analyzed with flow cytometry using propidium iodide (PI) and YO-PRO-1. NGF and the peptides showed a strong cytotoxic effect on U251 glioma cells in the MTT test (IC50 0.0214, 3.1, and 26.1 μM, respectively) compared to chemotherapy. The combination of PG-1 + etoposide had a synergistic effect on apoptosis of U251 glioma cells. It should be noted that the cells were in the early and late stages of apoptosis, respectively, compared with the control cells. The caspase-3 activation analysis revealed that the caspase-3 level was not significantly (p > 0.05) increased in U251 cells following PG-1 with etoposide treatment compared with that in the untreated cells, suggesting that the combination of PG-1 and etoposide may induce caspase-independent apoptosis in U251 cells. NGF, LL-37, and PG-1 represent promising drug candidates as the treatment regimen for GBM. Furthermore, the synergistic efficacy of the combined protocol using PG-1 and etoposide may overcome some of the typical limitations of the conventional therapeutic protocols, thus representing a promising approach for GBM therapy.

Quantifying dynamic pro-inflammatory gene expression and heterogeneity in single macrophage cells

Macrophages must respond appropriately to pathogens and other pro-inflammatory stimuli in order to perform their roles in fighting infection. One way in which inflammatory stimuli can vary is in their dynamics-that is, the amplitude and duration of stimulus experienced by the cell. In this study, we performed long-term live cell imaging in a microfluidic device to investigate how the pro-inflammatory genes IRF1, CXCL10, and CXCL9 respond to dynamic interferon-gamma (IFNγ) stimulation. We found that IRF1 responds to low concentration or short duration IFNγ stimulation, whereas CXCL10 and CXCL9 require longer or higherconcentration stimulation to be expressed. We also investigated the heterogeneity in the expression of each gene and found that CXCL10 and CXCL9 have substantial cell-to-cell variability. In particular, the expression of CXCL10 appears to be largely stochastic with a subpopulation of nonresponding cells across all the stimulation conditions tested. We developed both deterministic and stochastic models for the expression of each gene. Our modeling analysis revealed that the heterogeneity in CXCL10 can be attributed to a slow chromatin-opening step that is on a similar timescale to that of adaptation of the upstream signal. In this way, CXCL10 expression in individual cells can remain stochastic in response to each pulse of repeated stimulation, which we also validated by experiments. Together, we conclude that pro-inflammatory genes in the same signaling pathway can respond to dynamic IFNγ stimulus with very different response features and that upstream signal adaptation can contribute to shaping heterogeneous gene expression.

SETD1A drives stemness by reprogramming the epigenetic landscape in hepatocellular carcinoma stem cells

Cancer stem cells (CSCs) are responsible for tumor progression and recurrence. However, the mechanisms regulating hepatocellular carcinoma (HCC) stemness remain unclear. Applying a genome-scale CRISPR knockout screen, we identified that the H3K4 methyltransferase SETD1A and other members of Trithorax group proteins drive cancer stemness in HCC. SET domain containing 1A (SETD1A) was positively correlated with poor clinical outcome in patients with HCC. Combination of SETD1A and serum alpha fetoprotein substantially improved the accuracy of predicting HCC relapse. Mechanistically, SETD1A mediates transcriptional activation of various histone-modifying enzymes, facilitates deposition of trimethylated H3K4 (H3K4me3) and H3K27me3, and activates oncogenic enhancers and super-enhancers, leading to activation of oncogenes and inactivation of tumor suppressor genes simultaneously in liver CSCs. In addition, SETD1A cooperates with polyadenylate-binding protein cytoplasmic 1 to regulate H3K4me3 modification on oncogenes. Our data pinpoint SETD1A as a key epigenetic regulator driving HCC stemness and progression, highlighting the potential of SETD1A as a candidate target for HCC intervention and therapy.

Single-cell transcriptome analysis revealing the intratumoral heterogeneity of ccRCC and validation of MT2A in pathogenesis

Clear-cell renal cell carcinoma (ccRCC) appears as the most common type of kidney cancer, the carcinogenesis of which has not been fully elucidated. Tumor heterogeneity plays a crucial role in cancer progression, which could be largely deciphered by the implement of scRNA-seq. The bulk and single-cell RNA expression profile is obtained from TCGA and study conducted by Young et al. We utilized UMAP, TSNE, and clustering algorithm Louvain for dimensionality reduction and FindAllMarkers function for determining the DEGs. Monocle2 was utilized to perform pseudo-time series analysis. SCENIC was implemented for transcription factor analysis of each cell subgroup. A series of WB, CFA, CCK-8, and EDU analysis was utilized for the validation of the role of MT2A in ccRCC carcinogenesis. We observed higher infiltration of T/NK and B cells in tumorous tissues, indicating the role of immune cells in ccRCC carcinogenesis. Transcription factor analysis revealed the activation of EOMES and ETS1 in CD8 + T cells, while CAFs were divided into myo-CAFs and i-CAFs, with i-CAFs showing distinct enrichment of ATF3, JUND, JUNB, EGR1, and XBP1. Through cell trajectory analysis, we discerned three distinct stages of cellular evolution, where State2 symbolizes normal renal tubular cells that underwent transitions into State1 and State3 as the CNV score ascended. Functional enrichment examination revealed an amplification of interferon gamma and inflammatory response pathways within tumor cells. The consensus clustering algorithm yielded two molecular subtypes, with cluster 2 being associated with advanced tumor stages and an abundance of infiltrated immune cells. We identified 17 prognostic genes through Cox and LASSO regression models and used them to construct a prognostic model, the efficacy of which was verified in multiple cohorts. Furthermore, we investigated the role of MT2A, one of our hub genes, in ccRCC carcinogenesis, and found it to regulate proliferation and migration of malignant cells. We depicted a detailed single-cell landscape of ccRCC, with special focus on CAFs, endothelial cells, and renal tubular cells. A prognostic model of high stability and accuracy was constructed based on the DEGs. MT2A was found to be actively implicated in ccRCC carcinogenesis, regulating proliferation and migration of the malignant cells.

Unlocking the Molecular Secrets of Antifolate Drug Resistance: A Multi-Omics Investigation of the NCI-60 Cell Line Panel

Drug resistance continues to be a significant problem in cancer therapy, leading to relapse and associated mortality. Although substantial progress has been made in understanding drug resistance, significant knowledge gaps remain concerning the molecular underpinnings that drive drug resistance and which processes are unique to certain drug classes. The NCI-60 cell line panel program has evaluated the activity of numerous anticancer agents against many common cancer cell line models and represents a highly valuable resource to study intrinsic drug resistance. Furthermore, great efforts have been undertaken to collect high-quality omics datasets to characterize these cell lines. The current study takes these two sources of data-drug response and omics profiles-and uses a multi-omics investigation to uncover molecular networks that differentiate cancer cells that are sensitive or resistant to antifolates, which is a commonly used class of anticancer drugs. Results from a combination of univariate and multivariate analyses showed numerous metabolic processes that differentiate sensitive and resistant cells, including differences in glycolysis and gluconeogenesis, arginine and proline metabolism, beta-alanine metabolism, purine metabolism, and pyrimidine metabolism. Further analysis using multivariate and integrated pathway analysis indicated purine metabolism as the major metabolic process separating cancer cells sensitive or resistant to antifolates. Additional pathways differentiating sensitive and resistant cells included autophagy-related processes (e.g., phagosome, lysosome, autophagy, mitophagy) and adhesion/cytoskeleton-related pathways (e.g., focal adhesion, regulation of actin cytoskeleton, tight junction). Volcano plot analysis and the receiver operating characteristic (ROC) curves of top selected variables differentiating Q1 and Q4 revealed the importance of genes involved in the regulation of the cytoskeleton and extracellular matrix (ECM). These results provide novel insights toward mechanisms of intrinsic antifolate resistance as it relates to interactions between nucleotide metabolism, autophagy, and the cytoskeleton. These processes should be evaluated in future studies to potentially derive novel therapeutic strategies and personalized treatment approaches to improve antifolate response.

Advances in PET imaging of cancer

Molecular imaging has experienced enormous advancements in the areas of imaging technology, imaging probe and contrast development, and data quality, as well as machine learning-based data analysis. Positron emission tomography (PET) and its combination with computed tomography (CT) or magnetic resonance imaging (MRI) as a multimodality PET-CT or PET-MRI system offer a wealth of molecular, functional and morphological data with a single patient scan. Despite the recent technical advances and the availability of dozens of disease-specific contrast and imaging probes, only a few parameters, such as tumour size or the mean tracer uptake, are used for the evaluation of images in clinical practice. Multiparametric in vivo imaging data not only are highly quantitative but also can provide invaluable information about pathophysiology, receptor expression, metabolism, or morphological and functional features of tumours, such as pH, oxygenation or tissue density, as well as pharmacodynamic properties of drugs, to measure drug response with a contrast agent. It can further quantitatively map and spatially resolve the intertumoural and intratumoural heterogeneity, providing insights into tumour vulnerabilities for target-specific therapeutic interventions. Failure to exploit and integrate the full potential of such powerful imaging data may lead to a lost opportunity in which patients do not receive the best possible care. With the desire to implement personalized medicine in the cancer clinic, the full comprehensive diagnostic power of multiplexed imaging should be utilized.

Extended Exposure Topotecan Significantly Improves Long-Term Drug Sensitivity by Decreasing Malignant Cell Heterogeneity and by Preventing Epithelial-Mesenchymal Transition

Maximum tolerable dosing (MTD) of chemotherapeutics has long been the gold standard for aggressive malignancies. Recently, alternative dosing strategies have gained traction for their improved toxicity profiles and unique mechanisms of action, such as inhibition of angiogenesis and stimulation of immunity. In this article, we investigated whether extended exposure (EE) topotecan could improve long-term drug sensitivity by preventing drug resistance. To achieve significantly longer exposure times, we used a spheroidal model system of castration-resistant prostate cancer. We also used state-of-the-art transcriptomic analysis to further elucidate any underlying phenotypic changes that occurred in the malignant population following each treatment. We determined that EE topotecan had a much higher barrier to resistance relative to MTD topotecan and was able to maintain consistent efficacy throughout the study period (EE IC50 of 54.4 nM (Week 6) vs. MTD IC50 of 2200 nM (Week 6) vs. 83.8 nM IC50 for control (Week 6) vs. 37.8 nM IC50 for control (Week 0)). As a possible explanation for these results, we determined that MTD topotecan stimulated epithelial-mesenchymal transition (EMT), upregulated efflux pumps, and produced altered topoisomerases relative to EE topotecan. Overall, EE topotecan resulted in a more sustained treatment response and maintained a less aggressive malignant phenotype relative to MTD topotecan.

Intratumor heterogeneity and cell secretome promote chemotherapy resistance and progression of colorectal cancer

The major underlying cause for the high mortality rate in colorectal cancer (CRC) relies on its drug resistance, to which intratumor heterogeneity (ITH) contributes substantially. CRC tumors have been reported to comprise heterogeneous populations of cancer cells that can be grouped into 4 consensus molecular subtypes (CMS). However, the impact of inter-cellular interaction between these cellular states on the emergence of drug resistance and CRC progression remains elusive. Here, we explored the interaction between cell lines belonging to the CMS1 (HCT116 and LoVo) and the CMS4 (SW620 and MDST8) in a 3D coculture model, mimicking the ITH of CRC. The spatial distribution of each cell population showed that CMS1 cells had a preference to grow in the center of cocultured spheroids, while CMS4 cells localized at the periphery, in line with observations in tumors from CRC patients. Cocultures of CMS1 and CMS4 cells did not alter cell growth, but significantly sustained the survival of both CMS1 and CMS4 cells in response to the front-line chemotherapeutic agent 5-fluorouracil (5-FU). Mechanistically, the secretome of CMS1 cells exhibited a remarkable protective effect for CMS4 cells against 5-FU treatment, while promoting cellular invasion. Secreted metabolites may be responsible for these effects, as demonstrated by the existence of 5-FU induced metabolomic shifts, as well as by the experimental transfer of the metabolome between CMS1 and CMS4 cells. Overall, our results suggest that the interplay between CMS1 and CMS4 cells stimulates CRC progression and reduces the efficacy of chemotherapy.

Targeting unfolded protein response using albumin-encapsulated nanoparticles attenuates temozolomide resistance in glioblastoma

BACKGROUND

Chemoresistant cancer cells frequently exhibit a state of chronically activated endoplasmic reticulum (ER) stress. Engaged with ER stress, the unfolded protein response (UPR) is an adaptive reaction initiated by the accumulation of misfolded proteins. Protein disulfide isomerase (PDI) is a molecular chaperone known to be highly expressed in glioblastomas with acquired resistance to temozolomide (TMZ). We investigate whether therapeutic targeting of PDI provides a rationale to overcome chemoresistance.

METHODS

The activity of PDI was suppressed in glioblastoma cells using a small molecule inhibitor CCF642. Either single or combination treatment with TMZ was used. We prepared nanoformulation of CCF642 loaded in albumin as a drug carrier for orthotopic tumour model.

RESULTS

Inhibition of PDI significantly enhances the cytotoxic effect of TMZ on glioblastoma cells. More importantly, inhibition of PDI is able to sensitise glioblastoma cells that are initially resistant to TMZ treatment. Nanoformulation of CCF642 is well-tolerated and effective in suppressing tumour growth. It activates cell death-triggering UPR beyond repair and induces ER perturbations through the downregulation of PERK signalling. Combination treatment of TMZ with CCF642 significantly reduces tumour growth compared with either modality alone.

CONCLUSION

Our study demonstrates modulation of ER stress by targeting PDI as a promising therapeutic rationale to overcome chemoresistance.

Precision Medicine in Bladder Cancer: Present Challenges and Future Directions

Bladder cancer (BC) is characterized by significant histopathologic and molecular heterogeneity. The discovery of molecular pathways and knowledge of cellular mechanisms have grown exponentially and may allow for better disease classification, prognostication, and development of novel and more efficacious noninvasive detection and surveillance strategies, as well as selection of therapeutic targets, which can be used in BC, particularly in a neoadjuvant or adjuvant setting. This article outlines recent advances in the molecular pathology of BC with a better understanding and deeper focus on the development and deployment of promising biomarkers and therapeutic avenues that may soon make a transition into the domain of precision medicine and clinical management for patients with BC.

Oxidative Stress, Inflammation, Gut Dysbiosis: What Can Polyphenols Do in Inflammatory Bowel Disease?

Inflammatory bowel disease (IBD) is a long-term, progressive, and recurrent intestinal inflammatory disorder. The pathogenic mechanisms of IBD are multifaceted and associated with oxidative stress, unbalanced gut microbiota, and aberrant immune response. Indeed, oxidative stress can affect the progression and development of IBD by regulating the homeostasis of the gut microbiota and immune response. Therefore, redox-targeted therapy is a promising treatment option for IBD. Recent evidence has verified that Chinese herbal medicine (CHM)-derived polyphenols, natural antioxidants, are able to maintain redox equilibrium in the intestinal tract to prevent abnormal gut microbiota and radical inflammatory responses. Here, we provide a comprehensive perspective for implementing natural antioxidants as potential IBD candidate medications. In addition, we demonstrate novel technologies and stratagems for promoting the antioxidative properties of CHM-derived polyphenols, including novel delivery systems, chemical modifications, and combination strategies.

Evolution-Informed Strategies for Combating Drug Resistance in Cancer

The ever-changing nature of cancer poses the most difficult challenge oncologists face today. Cancer's remarkable adaptability has inspired many to work toward understanding the evolutionary dynamics that underlie this disease in hopes of learning new ways to fight it. Eco-evolutionary dynamics of a tumor are not accounted for in most standard treatment regimens, but exploiting them would help us combat treatment-resistant effectively. Here, we outline several notable efforts to exploit these dynamics and circumvent drug resistance in cancer.

Fibroblasts as Turned Agents in Cancer Progression

Differentiated epithelial cells reside in the homeostatic microenvironment of the native organ stroma. The stroma supports their normal function, their G0 differentiated state, and their expansion/contraction through the various stages of the life cycle and physiologic functions of the host. When malignant transformation begins, the microenvironment tries to suppress and eliminate the transformed cells, while cancer cells, in turn, try to resist these suppressive efforts. The tumor microenvironment encompasses a large variety of cell types recruited by the tumor to perform different functions, among which fibroblasts are the most abundant. The dynamics of the mutual relationship change as the sides undertake an epic battle for control of the other. In the process, the cancer "wounds" the microenvironment through a variety of mechanisms and attracts distant mesenchymal stem cells to change their function from one attempting to suppress the cancer, to one that supports its growth, survival, and metastasis. Analogous reciprocal interactions occur as well between disseminated cancer cells and the metastatic microenvironment, where the microenvironment attempts to eliminate cancer cells or suppress their proliferation. However, the altered microenvironmental cells acquire novel characteristics that support malignant progression. Investigations have attempted to use these traits as targets of novel therapeutic approaches.

scEvoNet: a gradient boosting-based method for prediction of cell state evolution

BACKGROUND

Exploring the function or the developmental history of cells in various organisms provides insights into a given cell type's core molecular characteristics and putative evolutionary mechanisms. Numerous computational methods now exist for analyzing single-cell data and identifying cell states. These methods mostly rely on the expression of genes considered as markers for a given cell state. Yet, there is a lack of scRNA-seq computational tools to study the evolution of cell states, particularly how cell states change their molecular profiles. This can include novel gene activation or the novel deployment of programs already existing in other cell types, known as co-option.

RESULTS

Here we present scEvoNet, a Python tool for predicting cell type evolution in cross-species or cancer-related scRNA-seq datasets. ScEvoNet builds the confusion matrix of cell states and a bipartite network connecting genes and cell states. It allows a user to obtain a set of genes shared by the characteristic signature of two cell states even between distantly-related datasets. These genes can be used as indicators of either evolutionary divergence or co-option occurring during organism or tumor evolution. Our results on cancer and developmental datasets indicate that scEvoNet is a helpful tool for the initial screening of such genes as well as for measuring cell state similarities.

CONCLUSION

The scEvoNet package is implemented in Python and is freely available from https://github.com/monsoro/scEvoNet . Utilizing this framework and exploring the continuum of transcriptome states between developmental stages and species will help explain cell state dynamics.

Increased Expression of the Pathological O-glycosylated Form of Oncofetal Fibronectin in the Multidrug Resistance Phenotype of Cancer Cells

Changes in protein glycosylation are a hallmark of transformed cells and modulate numerous phenomena associated with cancer progression, such as the acquisition of multidrug resistance (MDR) phenotype. Different families of glycosyltransferases and their products have already been described as possible modulators of the MDR phenotype. Among the glycosyltransferases intensively studied in cancer research, UDP-N-acetyl-D-galactosamine:polypeptide N-acetylgalactosaminyltransferase-6 (pp-GalNAc-T6), which is widely expressed in many organs and tissues, stands out. Its influence in several events associated with kidney, oral, pancreatic, renal, lung, gastric and breast cancer progression has already been described. However, its participation in the MDR phenotype has never been studied. Here, we demonstrate that human breast adenocarcinoma MCF-7 MDR cell lines, generated by chronic exposure to doxorubicin, in addition to exhibiting increased expression of proteins belonging to the ABC superfamily (ABCC1 and ABCG2), and anti-apoptotic proteins (Blcl-2 and Bcl-xL), also present high expression of pp-GalNAc-T6, the enzyme currently proposed as the main responsible for the biosynthesis of oncofetal fibronectin (onf-FN), a major extracellular matrix component expressed by cancer cells and embryonic tissues, but absent in healthy cells. Our results show that onf-FN, which is generated by the addition of a GalNAc unit at a specific threonine residue inside the type III homology connective segment (IIICS) domain of FN, is strongly upregulated during the acquisition of the MDR phenotype. Also, the silencing of pp-GalNAc-T6, not only compromises the expression of the oncofetal glycoprotein, but also made the MDR cells more sensitive to all anticancer drugs tested, partially reversing the MDR phenotype. Taken together, our results demonstrate for the first time the upregulation of the O-glycosylated oncofetal fibronectin, as well as the direct participation of pp-GalNAc-T6 during the acquisition of a MDR phenotype in a breast cancer model, giving credence to the hypothesis that in transformed cells, glycosyltransferases and/or their products, such as unusual extracellular matrix glycoproteins can be used as potential therapeutic targets for the treatment of cancer.

Artificial intelligence in cancer immunotherapy: Applications in neoantigen recognition, antibody design and immunotherapy response prediction

Cancer immunotherapy is a method of controlling and eliminating tumors by reactivating the body's cancer-immunity cycle and restoring its antitumor immune response. The increased availability of data, combined with advancements in high-performance computing and innovative artificial intelligence (AI) technology, has resulted in a rise in the use of AI in oncology research. State-of-the-art AI models for functional classification and prediction in immunotherapy research are increasingly used to support laboratory-based experiments. This review offers a glimpse of the current AI applications in immunotherapy, including neoantigen recognition, antibody design, and prediction of immunotherapy response. Advancing in this direction will result in more robust predictive models for developing better targets, drugs, and treatments, and these advancements will eventually make their way into the clinical setting, pushing AI forward in the field of precision oncology.

H3K27-altered diffuse midline glioma: a paradigm shifting opportunity in direct delivery of targeted therapeutics

INTRODUCTION

Despite much progress, the prognosis for H3K27-altered diffuse midline glioma (DMG), previously known as diffuse intrinsic pontine glioma when located in the brainstem, remains dark and dismal.

AREAS COVERED

A wealth of research over the past decade has revolutionized our understanding of the molecular basis of DMG, revealing potential targetable vulnerabilities for treatment of this lethal childhood cancer. However, obstacles to successful clinical implementation of novel therapies remain, including effective delivery across the blood-brain barrier (BBB) to the tumor site. Here, we review relevant literature and clinical trials and discuss direct drug delivery via convection-enhanced delivery (CED) as a promising treatment modality for DMG. We outline a comprehensive molecular, pharmacological, and procedural approach that may offer hope for afflicted patients and their families.

EXPERT OPINION

Challenges remain in successful drug delivery to DMG. While CED and other techniques offer a chance to bypass the BBB, the variables influencing successful intratumoral targeting are numerous and complex. We discuss these variables and potential solutions that could lead to the successful clinical implementation of preclinically promising therapeutic agents.

Exploiting Polyphenol-Mediated Redox Reorientation in Cancer Therapy

Polyphenol, one of the major components that exert the therapeutic effect of Chinese herbal medicine (CHM), comprises several categories, including flavonoids, phenolic acids, lignans and stilbenes, and has long been studied in oncology due to its significant efficacy against cancers in vitro and in vivo. Recent evidence has linked this antitumor activity to the role of polyphenols in the modulation of redox homeostasis (e.g., pro/antioxidative effect) in cancer cells. Dysregulation of redox homeostasis could lead to the overproduction of reactive oxygen species (ROS), resulting in oxidative stress, which is essential for many aspects of tumors, such as tumorigenesis, progression, and drug resistance. Thus, investigating the ROS-mediated anticancer properties of polyphenols is beneficial for the discovery and development of novel pharmacologic agents. In this review, we summarized these extensively studied polyphenols and discussed the regulatory mechanisms related to the modulation of redox homeostasis that are involved in their antitumor property. In addition, we discussed novel technologies and strategies that could promote the development of CHM-derived polyphenols to improve their versatile anticancer properties, including the development of novel delivery systems, chemical modification, and combination with other agents.

Clonal relationship and alcohol consumption-associated mutational signature in synchronous hypopharyngeal tumours and oesophageal squamous cell carcinoma

BACKGROUND

The patients with dual oesophageal squamous cell carcinoma (ESCC) and hypopharyngeal cancer (HPC) have poor prognosis; their underlying genetic pathogenesis is unclear. We hypothesise that development of synchronous ESCC/HPC depends on multicentricity or independent origin, rather than multifocality due to local or lateral spreading.

METHOD

Multiple region whole-exome sequencing (M-WES) and clonality analysis were used to assess clonal relationship and spatial inter- or intra-tumour heterogeneity (ITH) in 62 tumour regions from eight dual ESCC/HPC and ten ESCC patients.

RESULTS

All synchronous ESCC/HPC patients had COSMIC 16 mutation signatures, compared to only 40% ESCC in the current study (p = 0.013) and public data set (n = 165, p = 0.003). This alcohol consumption-related mutation signature 16, commonly involved in multiple alcohol-related cancers, was significantly associated with drinking and alcohol metabolism-related ADH1B rs1229984. The mutational landscape and copy number profiles were completely distinct between the two primary tumours; clonality analysis further suggested the two primary tumours shared no or only one clone accompanying independent subclone evolution. M-WES strategy demonstrated higher sensitivity and accuracy for detection of mutational prevalence and the late branch mutations among different regions in the ESCC tumours, compared to traditional sequencing analysis based on single biopsy strategy. Patients with high ITH assessed by cancer cell fraction analysis after M-WES were significantly associated with both relapse and survival.

CONCLUSIONS

Our hypothesis-generating M-WES ITH assessment data have implications for prognostication. Collectively, our findings support multicentric independent clonal evolution, the field cancerisation theory, and suggest novel insights implicating an aetiologic role of alcohol metabolism in dual ESCC/HPC carcinogenesis.

Immersion bioprinting of hyaluronan and collagen bioink-supported 3D patient-derived brain tumor organoids

Organoids, and in particular patient-derived organoids, have emerged as crucial tools for cancer research. Our organoid platform, which has supported patient-derived tumor organoids (PTOs) from a variety of tumor types, has been based on the use of hyaluronic acid (HA) and collagen, or gelatin, hydrogel bioinks. One hurdle to high throughput PTO biofabrication is that as high-throughput multi-well plates, bioprinted volumes have increased risk of contacting the sides of wells. When this happens, surface tension causes bioinks to fall flat, resulting in 2D cultures. To address this problem, we developed an organoid immersion bioprinting method-inspired by the FRESH printing method-in which organoids are bioprinted into support baths in well plates. The bath-in this case an HA solution-shields organoids from the well walls, preventing deformation. Here we describe an improvement to our approach, based on rheological assessment of previous gelatin baths versus newer HA support baths, combined with morphological assessment of immersion bioprinted organoids. HA print baths enabled more consistent organoid volumes and geometries. We optimized the printing parameters of this approach using a cell line. Finally, we deployed our optimized immersion bioprinting approach into a drug screening application, using PTOs derived from glioma biospecimens, and a lung adenocarcinoma brain metastasis. In these studies, we showed a general dose dependent response to an experimental p53 activator compound and temozolomide (TMZ), the drug most commonly given to brain tumor patients. Responses to the p53 activator compound were effective across all PTO sets, while TMZ responses were observed, but less pronounced, potentially explained by genetic and epigenetic states of the originating tumors. The studies presented herein showcase a bioprinting methodology that we hope can be used in increased throughput settings to help automate biofabrication of PTOs for drug development-based screening studies and precision medicine applications.

Very large hidden genetic diversity in one single tumor: evidence for tumors-in-tumor

Despite the concern of within-tumor genetic diversity, this diversity is in fact limited by the kinship among cells in the tumor. Indeed, genomic studies have amply supported the 'Nowell dogma' whereby cells of the same tumor descend from a single progenitor cell. In parallel, genomic data also suggest that the diversity could be >10-fold larger if tumor cells are of multiple origins. We develop an evolutionary hypothesis that a single tumor may often harbor multiple cell clones of independent origins, but only one would be large enough to be detected. To test the hypothesis, we search for independent tumors within a larger one (or tumors-in-tumor). Very high density sampling was done on two cases of colon tumors. Case 1 indeed has 13 independent clones of disparate sizes, many having heavy mutation burdens and potentially highly tumorigenic. In Case 2, despite a very intensive search, only two small independent clones could be found. The two cases show very similar movements and metastasis of the dominant clone. Cells initially move actively in the expanding tumor but become nearly immobile in late stages. In conclusion, tumors-in-tumor are plausible but could be very demanding to find. Despite their small sizes, they can enhance the within-tumor diversity by orders of magnitude. Such increases may contribute to the missing genetic diversity associated with the resistance to cancer therapy.

Single-cell sequencing technologies in bladder cancer research: Applications and challenges

Bladder cancer is among the most common malignant tumors with highly heterogeneous molecular characteristics. Despite advancements of the available therapeutic options, several bladder cancer patients exhibit unsatisfactory clinical outcomes. The lack of specific biomarkers for effective targeted therapy or immunotherapy remains a major obstacle in treating bladder cancer. The rapid development of single-cell techniques is transforming our understanding of the intra-tumoral heterogeneity, thereby providing us with a powerful high-throughput sequencing tool that can reveal tumorigenesis, progression, and invasion in bladder tumors. In this review, we summarise and discuss how single-cell sequencing technologies have been applied in bladder cancer research, to advance our collective knowledge on the heterogeneity of bladder tumor cells, as well as to provide new insights into the complex ecosystem of the tumor microenvironment. The application of single-cell approaches also uncovers the therapeutic resistance mechanism in bladder cancer and facilitates the detection of urinary-exfoliated tumor cells. Moreover, benefiting from the powerful technical advantages of single-cell techniques, several key therapeutic targets and prognostic models of bladder cancer have been identified. It is hoped that this paper can provide novel insights into the precision medicine of bladder cancer.

Advances in single-cell sequencing technology in the field of hepatocellular carcinoma

Tumors are a class of diseases characterized by altered genetic information and uncontrolled growth. Sequencing technology provide researchers with a better way to explore specific tumor pathogenesis. In recent years, single-cell sequencing technology has shone in tumor research, especially in the study of liver cancer, revealing phenomena that were unexplored by previous studies. Single-cell sequencing (SCS) is a technique for sequencing the cellular genome, transcriptome, epigenome, proteomics, or metabolomics after dissociation of tissues into single cells. Compared with traditional bulk sequencing, single-cell sequencing can dissect human tumors at single-cell resolution, finely delineate different cell types, and reveal the heterogeneity of tumor cells. In view of the diverse pathological types and complex pathogenesis of hepatocellular carcinoma (HCC), the study of the heterogeneity among tumor cells can help improve its clinical diagnosis, treatment and prognostic judgment. On this basis, SCS has revolutionized our understanding of tumor heterogeneity, tumor immune microenvironment, and clonal evolution of tumor cells. This review summarizes the basic process and development of single-cell sequencing technology and its increasing role in the field of hepatocellular carcinoma.

Single Cell RNA Sequencing: A New Frontier in Pancreatic Ductal Adenocarcinoma

Simple Summary

Pancreatic cancer has a very low survival rate for several reasons. One of those is primarily due to the difficulty in diagnosing it at an early stage. For this reason, it is important to refine our understanding of this disease to guide the development of new diagnostic and therapeutic modalities to combat this fatal illness. Here we attempt to provide a review of current progress in utilizing single-cell RNA sequencing (scRNA-seq) techniques in the molecular profiling of pancreatic ductal adenocarcinoma.

Abstract

Pancreatic ductal adenocarcinoma is a malignancy with a high mortality rate. It exhibits significant heterogeneity in metabolic pathways which are associated with its progression. In this review, we discuss the role of single cell RNA sequencing in unraveling the metabolic and clinical features of these highly malignant tumors.

Long-term resistance to 5-fluorouracil promotes epithelial-mesenchymal transition, apoptosis evasion, autophagy, and reduced proliferation rate in colon cancer cells

The drug, 5-fluorouracil (5FU) is a standard first-line treatment for colorectal cancer (CRC) patients. However, drug resistance acquisition remains an important challenge for effective clinical outcomes. Here, we established a long-term drug-resistant CRC model and explored the cellular events underlying 5FU resistance. We showed that 5FU-treated cells (HCT-116 5FUR) using a prolonged treatment protocol were significantly more resistant than parental cells. Likewise, cell viability and IC50 values were also observed to increase in HCT-116 5FUR cells when treated with increasing doses of oxaliplatin, indicating a cross-resistance mechanism to other cytotoxic agents. Moreover, HCT-116 5FUR cells exhibited metabolic and molecular changes, as evidenced by increased thymidylate synthase levels and upregulated mRNA levels of ABCB1. HCT-116 5FUR cells were able to overcome S phase arrest and evade apoptosis, as well as activate autophagy, as indicated by increased LC3B levels. Cells treated with low and high doses displayed epithelial-mesenchymal transition (EMT) features, as observed by decreased E-cadherin and claudin-3 levels, increased vimentin protein levels, and increased SLUG, ZEB2 and TWIST1 mRNA levels. Furthermore, HCT-116 5FUR cells displayed enhanced migration and invasion capabilities. Interestingly, we found that the 5FU drug-resistance gene signature is positively associated with the mesenchymal signature in CRC samples, and that ABCB1 and ZEB2 co-expressed at high levels could predict poor outcomes in CRC patients. Overall, the 5FU long-term drug-resistance model established here induced various cellular events, and highlighted the importance of further efforts to identify promising targets involved in more than one cellular event to successfully overcome drug-resistance.

A label-free technique to quantify and visualize gold nanoparticle accumulation at the single-cell level

Despite their wide bioapplications, potential health risks of gold nanoparticles (AuNPs) remain unclear. As a determinant of their risks, AuNP accumulation within a cell population is subject to cell-to-cell heterogeneity. Methods to simultaneously quantify and visualize intracellular AuNPs at the single-cell level are, however, lacking. Here we developed a novel label-free technique, based on hyperspectral imaging with enhanced darkfield microscopy (HSI-DFM), to visualize and quantify AuNP accumulation at the single-cell level. The identification ability of the hyperspectral libraries derived from extra- and intracellular AuNPs was compared. The spectral number in the libraries was optimized to maximize their identification ability while minimizing the identification time. In addition, a filtration method was established to merge spectral libraries from different cell lines based on their similarity. The intracellularly accumulated AuNPs as determined by HSI-DFM well correlated with those detected by inductively coupled plasma mass spectrometry. This validation allowed us to calculate the intracellular concentration of AuNPs at the single-cell level and to monitor the accumulation kinetics of AuNPs in living cells. The label-free method developed herein can be applied to other types of AuNPs differing in their physicochemical properties as well as other NPs, as long as they are detectable by HSI-DFM.

The prognostic value of 18F-FDG PET/CT intra-tumoural metabolic heterogeneity in pretreatment neuroblastoma patients

Background

Neuroblastoma (NB) is the most common tumour in children younger than 5 years old and notable for highly heterogeneous. Our aim was to quantify the intra-tumoural metabolic heterogeneity of primary tumour lesions by using ¹⁸F-FDG PET/CT and evaluate the prognostic value of intra-tumoural metabolic heterogeneity in NB patients.

Methods

We retrospectively enrolled 38 pretreatment NB patients in our study. ¹⁸F-FDG PET/CT images were reviewed and analyzed using 3D slicer software. The semi-quantitative metabolic parameters of primary tumour were measured, including the maximum standard uptake value (SUVmax), metabolic tumour volume (MTV), and total lesion glycolysis (TLG). The areas under the curve of cumulative SUV-volume histogram index (AUC-CSH index) was used to quantify intra-tumoural metabolic heterogeneity. The median follow-up was 21.3 months (range 3.6 - 33.4 months). The outcome endpoint was event-free survival (EFS), including progression-free survival and overall survival. Survival analysis was performed using Cox regression models and Kaplan Meier survival plots.

Results

In all 38 newly diagnosed NB patients, 2 patients died, and 17 patients experienced a relapse. The AUC-CSH_total (r=0.630, P<0.001) showed moderate correlation with the AUC-CSH_40%. In univariate analysis, chromosome 11q deletion (P=0.033), Children's Oncology Group (COG) risk grouping (P=0.009), bone marrow involvement (BMI, P=0.015), and AUC-CSH_total (P=0.007) were associated with EFS. The AUC-CSH_total (P=0.036) and BMI (P=0.045) remained significant in multivariate analysis. The Kaplan Meier survival analyses demonstrated that patients with higher intra-tumoural metabolic heterogeneity and BMI had worse outcomes (log-rank P=0.002).

Conclusion

The intra-tumoural metabolic heterogeneity of primary lesions in NB was an independent prognostic factor for EFS. The combined predictive effect of intra-tumoural metabolic heterogeneity and BMI provided prognostic survival information in NB patients.

New insights from the single-cell level: Tumor associated macrophages heterogeneity and personalized therapy

Tumor-associated macrophages (TAMs) are important immune cells in the tumor microenvironment, and their invasion in tumors is closely related to poor prognosis. Although TAMs are recognized as therapeutic targets, their heterogeneity makes studying tumor mechanism and developing drugs targeting TAMs difficult. The study of TAMs heterogeneity can be used to analyze the mechanism of tumor progression and drug resistance, and may provide possible treatment strategies for cancer patients. Single-cell RNA sequencing (scRNA-seq) can reveal the RNA expression profile for each TAM to distinguish heterogeneity, thereby providing a more efficient detection method and more accurate information for TAM-related studies. In this review, by summarizing the research progress in macrophage heterogeneity and other aspects of scRNA-seq over the past five years, we introduced the development of scRNA-seq technology and its application status in solid tumors, analyzed the advantages and selections of scRNA-seq in TAMs, and summarized the detailed specific research fields. To explore the mechanism of tumor progression and drug intervention from single cell level will provide new perspective for personalized treatment strategies targeting macrophages.

Applications and Achievements of Single-Cell Sequencing in Gastrointestinal Cancer

Gastrointestinal cancer represents a public health concern that seriously endangers human health. The emerging single-cell sequencing (SCS) technologies are different from the large-scale sequencing technologies which provide inaccurate data. SCS is a powerful tool for deciphering the single-cell resolutions of cellular and molecular landscapes, revealing the features of single-cell genomes, transcriptomes, and epigenomes. Recently, SCS has been applied in the field of gastrointestinal cancer research for clarifying the origin and heterogeneity of gastrointestinal cancer, acquiring micro-environmental information, and improving diagnostic and treatment methods. This review outlines the applications of SCS in gastrointestinal cancer research and summarizes the most recent advances in the field.

Single-cell sequencing: a promising approach for uncovering the mechanisms of tumor metastasis

Single-cell sequencing (SCS) is an emerging high-throughput technology that can be used to study the genomics, transcriptomics, and epigenetics at a single cell level. SCS is widely used in the diagnosis and treatment of various diseases, including cancer. Over the years, SCS has gradually become an effective clinical tool for the exploration of tumor metastasis mechanisms and the development of treatment strategies. Currently, SCS can be used not only to analyze metastasis-related malignant biological characteristics, such as tumor heterogeneity, drug resistance, and microenvironment, but also to construct metastasis-related cell maps for predicting and monitoring the dynamics of metastasis. SCS is also used to identify therapeutic targets related to metastasis as it provides insights into the distribution of tumor cell subsets and gene expression differences between primary and metastatic tumors. Additionally, SCS techniques in combination with artificial intelligence (AI) are used in liquid biopsy to identify circulating tumor cells (CTCs), thereby providing a novel strategy for treating tumor metastasis. In this review, we summarize the potential applications of SCS in the field of tumor metastasis and discuss the prospects and limitations of SCS to provide a theoretical basis for finding therapeutic targets and mechanisms of metastasis.

Single-cell characterization of malignant phenotypes and microenvironment alteration in retinoblastoma

Retinoblastoma (RB) is the most common primary intraocular malignancy of childhood. It is known that the tumor microenvironment (TME) regulates tumorigenesis and metastasis. However, how the malignant progression in RB is determined by the heterogeneity of tumor cells and TME remains uncharacterized. Here, we conducted integrative single-cell transcriptome and whole-exome sequencing analysis of RB patients with detailed pathological and clinical measurements. By single-cell transcriptomic sequencing, we profiled around 70,000 cells from tumor samples of seven RB patients. We identified that the major cell types in RB were cone precursor-like (CP-like) and MKI67+ cone precursor (MKI67+ CP) cells. By integrating copy number variation (CNV) analysis, we found that RB samples had large clonal heterogeneity, where the malignant MKI67+ CP cells had significantly larger copy number changes. Enrichment analysis revealed that the conversion of CP-like to MKI67+ CP resulted in the loss of photoreceptor function and increased cell proliferation ability. The TME in RB was composed of tumor-associated macrophages (TAMs), astrocyte-like, and cancer-associated fibroblasts (CAFs). Particularly, during the invasion process, TAMs created an immunosuppressive environment, in which the proportion of TAMs decreased, M1-type macrophage was lost, and the TAMs-related immune functions were depressed. Finally, we identified that TAMs regulated tumor cells through GRN and MIF signaling pathways, while TAMs self-regulated through inhibition of CCL and GALECTIN signaling pathways during the invasion process. Altogether, our study creates a detailed transcriptomic map of RB with single-cell characterization of malignant phenotypes and provides novel molecular insights into the occurrence and progression of RB.

Identification of ERCC8 as a novel cisplatin-resistant gene in esophageal cancer based on genome-scale CRISPR/Cas9 screening

Esophageal cancer (ESCA) is one of the most common malignant tumors of the digestive system worldwide. As a first-line drug for chemotherapy, cisplatin resistance is the major obstacle in the successful treatment of esophageal cancer. Previous studies largely failed to identify the key genes associated with cisplatin resistance. Hence, the aim of this study was to screen the cisplatin resistance-related genes of esophageal cancer using CRISPR/Cas9 gene-editing technology and Brunello iBar library. Of note, we identified ERCC8 as a novel cisplatin-resistant gene by high-throughput sequencing and cisplatin resistance assays. Based on KEGG and GO analysis, we hypothesized that the mechanism of ERCC8 involvement in cisplatin resistance is through binding to damaged DNA to perform nucleotide excision repair, contributing to the restoration of basic DNA functions and cellular life activities in ESCA. In addition, Cell proliferation and wound healing assay confirmed that ERCC8 had little effect on the proliferation and migration of esophageal cancer cells in vitro. Survival analysis showed that ERCC8 expression was not associated with OS, DSS, or FPI in patients with ESCA. Immuno-infiltration analysis indicated that increased ERCC8 expression is associated with NK cells, macrophages, T helper cells, Th1 cells, and Th2 cells. Collectively, ERCC8 may serve as a new biomarker for predicting cisplatin resistance and have the prospect of becoming an effective target for the clinical treatment of cisplatin resistance in ESCA.

EMT-mediated regulation of CXCL1/5 for resistance to anti-EGFR therapy in colorectal cancer

The emergence of RAS/RAF mutant clone is the main feature of EGFR inhibitor resistance in KRAS wild-type colon cancer. However, its molecular mechanism is thought to be multifactorial, mainly due to cellular heterogeneity. In order to better understand the resistance mechanism in a single clone level, we successfully isolated nine cells with cetuximab-resistant (CR) clonality from in vitro system. All CR cells harbored either KRAS or BRAF mutations. Characteristically, these cells showed a higher EMT (Epithelial to mesenchymal transition) signature, showing increased EMT markers such as SNAI2. Moreover, the expression level of CXCL1/5, a secreted protein, was significantly higher in CR cells compared to the parental cells. In these CR cells, CXCL1/5 expression was coordinately regulated by SNAI2/NFKB and transactivated EGFR through CXCR/MMPI/EGF axis via autocrine singling. We also observed that combined cetuximab/MEK inhibitor not only showed growth inhibition but also reduced the secreted amounts of CXCL1/5. We further found that serum CXCL1/5 level was positively correlated with the presence of RAS/RAF mutation in colon cancer patients during cetuximab therapy, suggesting its role as a biomarker. These data indicated that the application of serum CXCL1/5 could be a potential serologic biomarker for predicting resistance to EGFR therapy in colorectal cancer.

Optimal chemotherapy counteracts cancer adaptive resistance in a cell-based, spatially-extended, evolutionary model

Most aggressive cancers are incurable due to their fast evolution of drug resistance. We model cancer growth and adaptive response in a simplified cell-based (CB) setting, assuming a genetic resistance to two chemotherapeutic drugs. We show that optimal administration protocols can steer cells resistance and turned it into a weakness for the disease. Our work extends the population-based (PB) model proposed by Orlando et al. (Physical Biology, 2012), in which a homogeneous population of cancer cells evolves according to a fitness landscape. The landscape models three types of trade-offs, differing on whether the cells are more, less, or equal effective when generalizing resistance to two drugs as opposed to specializing to a single one. The CB framework allows us to include genetic heterogeneity, spatial competition, and drugs diffusion, as well as realistic administration protocols. By calibrating our model on Orlando et al.'s assumptions, we show that dynamical protocols that alternate the two drugs minimize the cancer size at the end of (or at mid-points during) treatment. These results significantly differ from those obtained with the homogeneous model---suggesting static protocols under the pro-generalizing and neutral allocation trade-offs---highlighting the important role of spatial and genetic heterogeneities. Our work is the first attempt to search for optimal treatments in a CB setting, a step forward toward realistic clinical applications.