Proliferation Rate Of Tumor Cells Research Articles

Effect of 5β-dihydrotestosterone on vasodilator function and on cell proliferation.

Aging is one of the main factors associated with cardiovascular diseases. Androgens exert beneficial effects on the cardiovascular system and testosterone (TES) replacement therapy improves cardiometabolic risk factors. However, TES is contraindicated in patients with prostate cancer due to its proliferative effects on prostatic tumor cells. Additionally, TES and its reduced metabolites 5α- and 5β-dihydrotestosterone (5α-DHT and 5β-DHT) exert vasodilatory effects. Since androgen levels decrease during aging and 5β-DHT lacks genomic effects, this study is focused on analyzing its effect on vasodilator function and the proliferation rate of prostatic tumor and vascular smooth muscle cells. To study the vascular function, mesenteric arteries from aged-orchidectomized Sprague-Dawley rats were used. Mesenteric segments were divided into one control (without treatment) and three groups with the androgens (10 nM, 30 min) to analyze: acetylcholine- and sodium nitroprusside-induced responses and nitric oxide and superoxide anion production. To analyze cell proliferation, the effect of androgens on cell viability was determined. The results showed that 5β-DHT improves vasodilator function in arteries from aged-orchidectomized rats and induces antioxidant action, while the proliferation rate of the androgen-dependent prostatic tumor cells remains unaltered. These results make 5β-DHT a promising therapeutic agent for the treatment of cardiovascular pathologies.

An Enzyme-Responsive Self-Immolative Recognition Marker for Manipulating Cell-Cell Interactions.

The development of innovative strategies for cell membranes engineering is of prime interest to explore and manipulate cell-cell interactions. Herein, an enzyme-sensitive recognition marker that can be introduced on cell surface via bioorthogonal chemistry is designed. Once functionalized in this fashion, the cells gain the ability to assemble with cell partners coated with the complementary marker through non-covalent click chemistry. The artificial cell adhesion induces natural biological processes associated with cell proximity such as inhibiting cancer cell proliferation and migration. On the other hand, the enzymatic activation of the stimuli-responsive marker triggers the disassembly of cells, thereby restoring the tumor cell proliferation and migration rates. Thus, the study shows that the ready-to-use complementary markers are valuable tools for controlling the formation and the breaking of bonds between cells, offering an easy way to investigate biological processes associated to cell proximity.

Abstract 217: Establishment of a spatially defined co-culture model of non-small cell lung cancer organoids and cancer-associated fibroblasts to investigate phenotypic heterogeneity

Abstract Background: Cancer-associated fibroblasts (CAFs) are heterogeneous, with CAF subtypes being localized in spatially defined areas of tumors. However, it remains unclear which CAF subsets specifically play a role in fundamental processes such as tumor growth, invasion, and response to therapy. This study aims to establish a novel in vitro model that recapitulates the in vivo tumor-stroma spatial relationship to investigate CAF heterogeneity and its impact on tumor cell growth in non-small cell lung cancer (NSCLC). Methods: The in vitro model was established using NSCLC patient-derived CAFs and tumor organoids as a 6:1 ratio. Tumor cells originating from xenograft-derived organoids (XDOs) were embedded in a hydrogel containing CAFs (Day 0) and co-cultured for 5 days. Confocal microscopy was utilized to characterize and measure the proliferation of the XDO tumor cells in the co-culture setup, and the proliferation rate was defined as differences in tumor spheroid area between Day 1 and 5. Single-cell RNA-sequencing (scRNAseq) and gene set enrichment analysis (GSEA) were then used to assess the gene expression and signaling pathways dominant in mono- and co-culture to characterize CAF heterogeneity in this model. Results: Initially, the culture media formulations and the matrix for the growth of both CAFs and tumor cells were screened to assess the compatibility of different culture elements. Both CAFs and XDO tumor cells proliferated well in reduced organoid media (M27RD). This reduced medium and the novel matrix composition (50% Matrigel/50% Rat Tail type I collagen) also allowed for maintaining CAF contractility and XDO proliferation. Utilizing these harmonized media and matrix conditions, a spatially defined co-culture model, which incorporated XDOs as a central cluster surrounded by CAFs, was generated. In confocal microscopy, the proliferation rate of tumor cells was significantly higher in co-cultures with CAFs (adjusted p-value < 0.01), while not significant in mono-culture of tumor cells. The GSEA using the Hallmark gene sets on scRNAseq data generated in three co-cultures identified the heterogeneity among CAFs: two CAFs showed significantly higher effect on tumor cell proliferation with the most highly differential expressed genes (DEGs) enriched with inflammation and mitosis and the top high DEGs associated with epithelial-mesenchymal transition, while the other CAF has no effect. Conclusion: The harmonized co-culture conditions for NSCLC organoids and CAFs enabled the characterization of both cell phenotypes and the building of an informed model architecture to study tumor-stroma communication. The presence of CAFs increased tumor cell growth with enrichment in secreted proteins involved in epithelial-mesenchymal transition. Citation Format: Cheol-Kyu Park, Roya Navab, Elisa D'Arcangelo, Quan Li, Hiroyuki Ogawa, Nikolina Radulovich, Nhu-An Pham, Ming-Sound Tsao. Establishment of a spatially defined co-culture model of non-small cell lung cancer organoids and cancer-associated fibroblasts to investigate phenotypic heterogeneity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 217.

Sclerostin Alters Tumor Cell Characteristics of Oral Squamous Cell Carcinoma and May Be a Key Player in Local Bone Invasion.

Localized jawbone invasion is a milestone in the progression of oral squamous cell carcinoma (OSCC). The factors that promote this process are not well understood. Sclerostin is known to be involved in bone metabolism and there are preliminary reports of its involvement in bone tumors and bone metastasis. To identify a possible involvement of sclerostin in the bone invasion process of OSCC, sclerostin expression was analyzed in vitro in two different human OSCC tumor cell lines by quantitative real-time polymerase chain reaction (qRT-PCR), and the effect of recombinant human (rh)-sclerostin treatment on tumor cell capabilities was evaluated using proliferation, migration, and invasion assays. Undifferentiated human mesenchymal stem cells (hMSCs) were osteogenically differentiated and co-cultured with OSCC tumor cells to demonstrate potential interactions and migration characteristics. Sclerostin expression was evaluated in clinical cases by immunohistochemistry at the OSCC-jawbone interface in a cohort of 15 patients. Sclerostin expression was detected in both OSCC tumor cell lines in vitro and was also detected at the OSCC-jawbone interface in clinical cases. Tumor cell proliferation rate, migration and invasion ability were increased by rh-sclerostin treatment. The migration rate of tumor cells co-cultured with osteogenically differentiated hMSCs was increased. The results presented are the first data suggesting a possible involvement of sclerostin in the bone invasion process of OSCC, which deserves further investigation and may be a potential approach for drug-based tumor therapy.

Doxorubicin and folic acid-loaded zinc oxide nanoparticles-based combined anti-tumor and anti-inflammatory approach for enhanced anti-cancer therapy

BackgroundZinc oxide nanoparticles (ZnONPs) have impressively shown their efficacy in targeting and therapy of cancer. The present research was designated to investigate the potential of ZnONP nanocomposites as a cancer chemotherapeutic-based drug delivery system and to assess the anti-tumor and anti-inflammatory effectiveness of ZnONP nanocomposites combination with systemic chemotherapeutic drugs doxorubicin (DOX) and folic acid (FA) in Ehrlich ascites carcinoma (EAC) tumor cell line both in vitro and in vivo.MethodsAnti-tumor potential of ZnONP nanocomposites: ZnONPs, ZnONPs/FA, ZnONPs/DOX and ZnONPs/DOX/FA against EAC tumor cell line was evaluated in vitro by MTT assay. Anti-tumor and anti-inflammatory efficacy of ZnONP nanocomposites were analyzed in vivo by examination of the proliferation rate and apoptosis rate of EAC tumor cells by flow cytometry, splenocytes count, level of inflammatory markers interleukin 6 (IL-6) and tumor necrosis factor alpha (TNF-α), as well as liver and kidney function in EAC-challenged mice.ResultsIn vitro results showed that ZnONP nanocomposites showed a high anti-proliferative potency against EAC tumor cells. Furthermore, the in vivo study revealed that the treatment EAC-challenged mice with ZnONPs, ZnONPs/DOX, ZnONPs/FA and ZnONPs/DOX/FA hindered the proliferation rate of implanted EAC tumor cells through lowering their number and increasing their apoptosis rate. Moreover, the treatment of EAC-challenged mice with ZnONPs/DOX/FA markedly decreased the level of IL-6 and TNF-α and remarkably ameliorated the liver and kidney damages that were elevated by implantation of EAC tumor cells, restoring the liver and kidney functions to be close to the naïve mice control.ConclusionZnONP nanocomposites may be useful as a cancer chemotherapeutic-based drug delivery system. ZnONP nanocomposites: ZnONPs/DOX, ZnONPs/FA and ZnONPs/DOX/FA regimen may have anti-inflammatory approaches and a great potential to increase anti-tumor effect of conventional chemotherapy, overcoming resistance to cancer systemic chemotherapeutics and reducing their side effects, offering a promising regimen for cancer therapy.

CNSC-38. CHARACTERIZATION OF THE FUNCTIONAL RELEVANCE OF INTRA- AND INTERTUMORAL NETWORKS IN PRIMARY BREAST CANCER

Abstract Despite intensive efforts to improve current therapeutical strategies, breast cancer continues to be a life-shortening diagnosis for a significant number of affected women. Considering that the innervation density of breast cancers negatively correlates with the prognosis, the emerging field of Cancer Neuroscience, which deals with the reciprocal interactions between the nervous system and cancer cells, represents an attractive novel research direction. In fact, studies on breast cancer brain metastases have proven that the metastatic cells receive growth stimuli by hijacking healthy glutamatergic synapses. Beyond being capable of forming direct glutamatergic cancer-neuron synapses, primary brain tumor cells also connect to a multicellular intercommunicating network that contributes to therapy resistance. Whether similar mechanisms also apply to tumors outside the brain – accountable for the majority of cancer cases – remains unknown. Here, we aim at unraveling the functional role of intratumoral networks and the influence of (potential) direct primary breast cancer cell-neuron interactions. We hypothesize that purinergic signaling as a universal synaptic signaling mechanism enhances tumor growth. Through the application of ex vivo whole-organ tissue-clearing and nerve-labeling approaches, we noticed prevalent sensory and sympathetic innervation in the healthy and diseased murine mammary gland. Furthermore, we measured tumor cell proliferation rates in an in vitro model of primary murine sensory DRG-neurons co-cultured with breast cancer stem cells and compared these to monoculture controls. By implanting a mammary imaging window over the growing primary tumor, we longitudinally track the calcium activity of breast cancer cells in their natural microenvironment in the living mouse. We thereby are able to record co-activity of neighboring cells indicative of intratumoral network communication in primary breast cancers. Overall, our data support the existence of functional intra- and intertumoral breast cancer cell networks as an alternative therapeutical target. Future work needs to concentrate on unequivocally detecting direct neuron-cancer cell contacts.

3D vascularized microphysiological system for investigation of tumor-endothelial crosstalk in anti-cancer drug resistance

Despite the advantages of microfluidic system in drug screening, vascular systems responsible for the transport of drugs and nutrients have been hardly considered in the microfluidic-based chemotherapeutic screening. Considering the physiological characteristics of highly vascularized urinary tumors, we here investigated the chemotherapeutic response of bladder tumor cells using a vascularized tumor on a chip. The microfluidic chip was designed to have open-top region for tumor sample introduction and hydrophilic rail for spontaneous hydrogel patterning, which contributed to the construction of tumor-hydrogel-endothelium interfaces in a spatiotemporal on-demand manner. Utilizing the chip where intravascularly injected cisplatin diffuse across the endothelium and transport into tumor samples, chemotherapeutic responses of cisplatin-resistant or -susceptible bladder tumor cells were evaluated, showing the preservation of cellular drug resistance even within the chip. The open-top structure also enabled the direct harvest of tumor samples and post analysis in terms of secretome and gene expressions. Comparing the cisplatin efficacy of the cisplatin-resistant tumor cells in the presence or absence of endothelium, we found that the proliferation rates of tumor cells were increased in the vasculature-incorporated chip. These have suggested that our vascularized tumor chip allows the establishment of vascular-gel-tumor interfaces in spatiotemporal manners and further enables investigations of chemotherapeutic screening.

WDR74 serves as a novel therapeutic target by its oncogenic role in hepatocellular carcinoma

BackgroundHepatocellular carcinoma (HCC) is one of the most refractory human malignancies. WD repeat-containing protein 74 (WDR74) is involved in the tumorigenesis of various cancers, however, its clinical implications and biological function in HCC have yet to be clearly determined. MethodsBioinformatics analysis was conducted using various databases, including The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and UALCAN. The expression of WDR74 was confirmed in HCC tumor samples and the corresponding adjacent nontumor samples by qRT-PCR, western blot and immunohistochemistry. Functional enrichment analysis was used for the biological function prediction. In vitro experiments were performed to determine the effects of WDR74 on HCC cell proliferation. ResultsOur findings revealed that WDR74 was markedly upregulated in HCC tissues. Increased WDR74 expression had an unfavorable overall survival (OS). Multivariate Cox regression analysis demonstrated that WDR74 was an independent prognostic factor for OS in patients with HCC. Functional enrichment analysis suggested a significant correlation with cytokine-cytokine receptor interaction pathway in both TCGA-LIHC and GSE112790 datasets. Gene set enrichment analysis showed that WDR74 is probably involved in several pathways, such as MYC targets, ribosome, translation, and cell cycle. Finally, WDR74 knockdown reduced HCC cell proliferation by restraining the G1/S cell cycle transition and inducing apoptosis. ConclusionsThe current study demonstrates that elevated WDR74 expression is linked to an accelerated rate of tumor cell proliferation and is indicative of a poorer outcome in patients with HCC. Therefore, WDR74 could be used as a reliable prognostic biomarker and is a potential therapeutic target for HCC.

TFAM knockdown undermines SQSTM1 mRNA stability but retards autophagy flux and inhibits tumor cells proliferation under starvation conditions.

Although starvation stress can alter the homeostasis of mitochondria and promote autophagy, there is still a lack of research focusing on the connection between them. In this study, we found that, accompanied by the upregulation of autophagy flux, the membrane mitochondrial potential (MMP), the content of reactive oxygen species (ROS), the production of ATP, and the copy number of mitochondrial DNA (mt-DNA) were changed when limiting amino acids supply. We screened and analyzed altered genes related to mitochondrial homeostasis under starvation stress and verified that the expression of mitochondrial transcription factor A (TFAM) was prominently upregulated. Inhibition of TFAM led to the change of mitochondrial function and homeostasis, caused the decrease of SQSTM1 mRNA stability and ATG101 protein level and restricted the autophagy process of cells under amino acid deficient conditions. In addition, the TFAM knockdown and starvation treatment aggravated the DNA damage and reduced proliferation rate of tumor cells. Therefore, our data shows the correlation between mitochondria homeostasis and autophagy, reveals the effect of TFAM on autophagy flux under starvation stress and provides experimental basis for the combined starvation therapy targeting mitochondria to inhibit tumor growth.

Abstract P1-13-05: Extracellular vesicles-transported lncRNA BCDR1 promotes tumor cell proliferation and therapy resistance via upregulating G1/S-phase transition in breast cancer

Abstract Background Extracellular vesicles (EVs), secreted by tumor cells for intercellular communication, play an important role in breast cancer progression. Previous studies have proved that lncRNA could use EVs to transmit signals and affect the progression and treatment of breast cancer. In addition, a previous study has found that, in HER2 therapy-resistant tumors, CDK4/6 activity and cell cycle progression genes were involved and might serve as treatment targets. However, recent clinical trials were not supportive of the use of CDK4/6 inhibitors in HER2 enriched internal subtypes of breast cancer. In this study, we aim to explore the role of EVs-transported long noncoding RNA BCDR1 in the promotion of cell cycle progression in HER2-positive breast cancer, exploring a new potential target in combination with CDK4/6 inhibitor and anti-HER2 treatment. Methods Samples were collected from patients with HER2 overexpression receiving neoadjuvant therapy. RNA-seq was performed to identify differentially expressed RNAs between pathological complete response (pCR) and non-pCR group. In addition, serum extracellular vesicles were collected and determined through RNA-seq. The drug response and proliferation rate of tumor cells were measured in breast cancer cells (HCC-1954, BT-474 and MCF-7). Quantitative RT-PCR (qRT-PCR) was used to detect the expression levels of BCDR1 and its potential target genes. RNA-seq and GSEA analysis was carried out to determine the target pathways regulated by BCDR1. DNA fiber assay, mass spectrometry, and flow cytometry were used to understand the underlying mechanism of BCDR1. Results Core needle biopsy tissues from HER2-positive breast cancer patients with any ER status were collected before NAC. Among genes differentially overexpressed, BCDR1 was found to be downregulated in pCR group compared with non-pCR group. BCDR1 was also elevated in plasma EVs in the non-pCR group. In addition, overexpression of BCDR1 in breast cancer cells promoted cell proliferation and HER2 treatment resistance. Through pathway analysis, we found BCDR1 could facilitate G1/S-phase transition. Flow cytometry confirmed these findings. We also noticed that proteins that regulate DNA licensing including minichromosome maintenance proteins (MCMs) were enriched in BCDR1 overexpression cells. Through DNA fiber assay, we confirmed that BCDR1 could promote DNA replication initiation. Interestingly, under CDK4/6 inhibitor treatment, BCDR1 was induced, unrevealing an internal treatment-resistant mechanism in these tumor cells. Through EVs RT-qPCR, we found BCDR1 could transport from high expression cells to low, with the same biological function. We also explored antisense oligonucleotide (ASO) use in the inhibition of BCDR1 biological function and transportation. Conclusion BCDR1 promotes cell proliferation and therapy resistance via upregulating DNA licensing in breast cancer. BCDR1 could transported through EVs with same biological function. This study also suggests that BCDR1 could serve as a biomarker and therapeutic target in breast cancer. Citation Format: Qi Zhang, Bingqiu Xiu, Yayun Chi, Jiong Wu. Extracellular vesicles-transported lncRNA BCDR1 promotes tumor cell proliferation and therapy resistance via upregulating G1/S-phase transition in breast cancer [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P1-13-05.

Targeting of Glucose Transport and the NAD Pathway in Neuroendocrine Tumor (NET) Cells Reveals New Treatment Options

(1) Background: the potency of drugs that interfere with glucose metabolism, i.e., glucose transporters (GLUT) and nicotinamide phosphoribosyltransferase (NAMPT) was analyzed in neuroendocrine tumor (NET, BON-1, and QPG-1 cells) and small cell lung cancer (SCLC, GLC-2, and GLC-36 cells) tumor cell lines. (2) Methods: the proliferation and survival rate of tumor cells was significantly affected by the GLUT-inhibitors fasentin and WZB1127, as well as by the NAMPT inhibitors GMX1778 and STF-31. (3) Results: none of the NET cell lines that were treated with NAMPT inhibitors could be rescued with nicotinic acid (usage of the Preiss-Handler salvage pathway), although NAPRT expression could be detected in two NET cell lines. We finally analyzed the specificity of GMX1778 and STF-31 in NET cells in glucose uptake experiments. As previously shown for STF-31 in a panel NET-excluding tumor cell lines, both drugs specifically inhibited glucose uptake at higher (50 μM), but not at lower (5 μM) concentrations. (4) Conclusions: our data suggest that GLUT and especially NAMPT inhibitors are potential candidates for the treatment of NET tumors.

Analysis of the expression and prognostic significance of DDK complex in Hepatocarcinoma

BackgroundHepatocellular carcinoma (HCC) remains one of the most common and lethal malignancies worldwide. Although DBF4-dependent kinase (DDK) complex composed of CDC7 kinase and its regulatory subunit DBF4 has been shown to be overexpressed in primary tumors and promotes tumor development, while its role and prognostic value in HCC remain largely unknown. In the present study, the expression of DBF4 and CDC7 and their relationship with clinical characteristics were comprehensively analyzed.MethodsThe mRNA expression profiles of HCC and the corresponding clinical data of HCC patients were downloaded from TCGA and GEO databases, respectively. The differences in DBF4 and CDC7 expression in tumor tissues and adjacent normal tissues were analyzed. HCC-derived tissue microarray (TMA) was used to evaluate and score the expression of CDC7 by immunohistochemistry (IHC) staining. The Kaplan–Meier method and the Cox regression method were used to analyze the relationship between overall survival and clinical characteristics of the patients. Gene set enrichment analysis (GSEA) was used to analyze the pathway enrichment of DBF4 and CDC7.ResultsDBF4 and CDC7 had similar expression patterns in HCC patients. Detailly, compared with adjacent tissues, both mRNA and protein of DBF4 and CDC7 were significantly higher in HCC, and their expression was positively correlated with AJCC_T stage, clinical stage and G stage (grade) of liver cancer patients, and higher DBF4 or CDC7 expression predicted a worse prognosis in HCC patients with shorter overall survival (OS), recurrence-free survival (RFS), disease-specific survival (DSS) and progress-free survival (PFS). Cox regression analysis suggested that both DBF4 and CDC7 were independent risk factors for the prognosis of HCC patients in TCGA dataset. GSEA suggested that both DBF4 and CDC7 were positively correlated with cell cycle and DNA replication. Finally, the prognostic value of CDC7 was furtherly confirmed by TMA-based IHC staining results.ConclusionsOur study showed that DDK complex was significantly increased in HCC. Both DBF4 and CDC7 may be potential diagnostic and prognostic markers for HCC, and high expression of DDK members predicts a worse prognosis in patients with HCC, which may be associated with high tumor cell proliferation rate.

Doublecortin-like kinase 2 promotes breast cancer cell invasion and metastasis.

Doublecortin-like kinase 2 (DCLK2) is a microtubule-associated protein kinase that participates in neural development and maturation; however, whether it is involved in tumour progression remains unclear. DCLK2 overexpression and knockdown clones were established by lentivirus transfection. Western blot, PCR assays and bioinformatics analyses were conducted to observe the expression of DCLK2. CCK8, colony formation, scratch migration and Transwell assays were used to detect cell proliferation, migration and invasion, respectively. Tumour metastasis was evaluated in vivo using a tail vein metastasis model. Bioinformatics analyses were performed to analyse the expression correlation between DCLK2 and TCF4, or EMT markers in breast cancer. Our data indicate that DCLK2 is highly expressed in breast cancer cells and is associated with poor prognosis. Silencing DCLK2 does not affect the proliferation rate of tumour cells, but significantly suppresses migration and invasion as well as lung metastasis processes. Overexpression of DCLK2 can enhance the migratory and invasive abilities of normal breast epithelial cells. Moreover, TCF4/β-catenin inhibitor LF3 downregulates the expression of DCLK2 and inhibits the migration and invasion of breast cancer cells. Furthermore, we found that the downregulation of DCLK2 blocks the epithelial-mesenchymal transition (EMT) process. Our study indicates that DCLK2 plays an important role in EMT, cell invasion and metastasis, suggesting that DCLK2 is a potential target for the treatment of metastatic breast cancer.

Sources of inter-individual variability leading to significant changes in anti-PD-1 and anti-PD-L1 efficacy identified in mouse tumor models using a QSP framework.

While anti-PD-1 and anti-PD-L1 [anti-PD-(L)1] monotherapies are effective treatments for many types of cancer, high variability in patient responses is observed in clinical trials. Understanding the sources of response variability can help prospectively identify potential responsive patient populations. Preclinical data may offer insights to this point and, in combination with modeling, may be predictive of sources of variability and their impact on efficacy. Herein, a quantitative systems pharmacology (QSP) model of anti-PD-(L)1 was developed to account for the known pharmacokinetic properties of anti-PD-(L)1 antibodies, their impact on CD8+ T cell activation and influx into the tumor microenvironment, and subsequent anti-tumor effects in CT26 tumor syngeneic mouse model. The QSP model was sufficient to describe the variability inherent in the anti-tumor responses post anti-PD-(L)1 treatments. Local sensitivity analysis identified tumor cell proliferation rate, PD-1 expression on CD8+ T cells, PD-L1 expression on tumor cells, and the binding affinity of PD-1:PD-L1 as strong influencers of tumor growth. It also suggested that treatment-mediated tumor growth inhibition is sensitive to T cell properties including the CD8+ T cell proliferation half-life, CD8+ T cell half-life, cytotoxic T-lymphocyte (CTL)-mediated tumor cell killing rate, and maximum rate of CD8+ T cell influx into the tumor microenvironment. Each of these parameters alone could not predict anti-PD-(L)1 treatment response but they could shift an individual mouse's treatment response when perturbed. The presented preclinical QSP modeling framework provides a path to incorporate potential sources of response variability in human translation modeling of anti-PD-(L)1.

MTORC1-c-Myc pathway rewires methionine metabolism for HCC progression through suppressing SIRT4 mediated ADP ribosylation of MAT2A

BackgroundExploiting cancer metabolism during nutrient availability holds immense potential for the clinical and therapeutic benefits of hepatocellular carcinoma (HCC) patients. Dietary methionine is a metabolic dependence of cancer development, but how the signal transduction integrates methionine status to achieve the physiological demand of cancer cells remains unknown.MethodsLow or high levels of dietary methionine was fed to mouse models with patient-derived xenograft or diethyl-nitrosamine induced liver cancer. RNA sequence and metabolomics were performed to reveal the profound effect of methionine restriction on gene expression and metabolite changes. Immunostaining, sphere formation assays, in vivo tumourigenicity, migration and self-renewal ability were conducted to demonstrate the efficacy of methionine restriction and sorafenib.ResultsWe discovered that mTORC1-c-Myc-SIRT4 axis was abnormally regulated in a methionine-dependent manner and affected the HCC progression. c-Myc rewires methionine metabolism through TRIM32 mediated degradation of SIRT4, which regulates MAT2A activity by ADP-ribosylation on amino acid residue glutamic acid 111. MAT2A is a key enzyme to generate S-adenosylmethionine (SAM). Loss of SIRT4 activates MAT2A, thereby increasing SAM level and dynamically regulating gene expression, which triggers the high proliferation rate of tumour cells. SIRT4 exerts its tumour suppressive function with targeted therapy (sorafenib) by affecting methionine, redox and nucleotide metabolism.ConclusionsThese findings establish a novel characterization of the signaling transduction and the metabolic consequences of dietary methionine restriction in malignant liver tissue of mice. mTORC1, c-Myc, SIRT4 and ADP ribosylation site of MAT2A are promising clinical and therapeutic targets for the HCC treatment.

Targeting PI3K/Akt signaling in prostate cancer therapy.

Urological cancers have obtained much attention in recent years due to their mortality and morbidity. The most common and malignant tumor of urological cancers is prostate cancer that imposes high socioeconomic costs on public life and androgen-deprivation therapy, surgery, and combination of chemotherapy and radiotherapy are employed in its treatment. PI3K/Akt signaling is an oncogenic pathway responsible for migration, proliferation and drug resistance in various cancers. In the present review, the role of PI3K/Akt signaling in prostate cancer progression is highlighted. The activation of PI3K/Akt signaling occurs in prostate cancer, while PTEN as inhibitor of PI3K/Akt shows down-regulation. Stimulation of PI3K/Akt signaling promotes survival of prostate tumor cells and prevents apoptosis. The cell cycle progression and proliferation rate of prostate tumor cells increase by PI3K/Akt signaling induction. PI3K/Akt signaling stimulates EMT and enhances metastasis of prostate tumor cells. Silencing PI3K/Akt signaling impairs growth and metastasis of prostate tumor cells. Activation of PI3K/Akt signaling mediates drug resistance and reduces radio-sensitivity of prostate tumor cells. Anti-tumor compounds suppress PI3K/Akt signaling in impairing prostate tumor progression. Furthermore, upstream regulators such as miRNAs, lncRNAs and circRNAs regulate PI3K/Akt signaling and it has clinical implications for prostate cancer patients.

Deep learning characterization of brain tumours with diffusion weighted imaging

Glioblastoma multiforme (GBM) is one of the most deadly forms of cancer. Methods of characterizing these tumours are valuable for improving predictions of their progression and response to treatment. A mathematical model called the proliferation-invasion (PI) model has been used extensively in the literature to model the growth of these tumours, though it relies on known values of two key parameters: the tumour cell diffusivity and proliferation rate. Unfortunately, these parameters are difficult to estimate in a patient-specific manner, making personalized tumour forecasting challenging. In this paper, we develop and apply a deep learning model capable of making accurate estimates of these key GBM-characterizing parameters while simultaneously producing a full prediction of the tumour progression curve. Our method uses two sets of multi sequence MRI in order to produce estimations and relies on a preprocessing pipeline which includes brain tumour segmentation and conversion to tumour cellularity. We first apply our deep learning model to synthetic tumours to showcase the model’s capabilities and identify situations where prediction errors are likely to occur. We then apply our model to a clinical dataset consisting of five patients diagnosed with GBM. For all patients, we derive evidence-based estimates for each of the PI model parameters and predictions for the future progression of the tumour, along with estimates of the parameter uncertainties. Our work provides a new, easily generalizable method for the estimation of patient-specific tumour parameters, which can be built upon to aid physicians in designing personalized treatments.

DNAAF5 promotes hepatocellular carcinoma malignant progression by recruiting USP39 to improve PFKL protein stability.

PurposesDynein axonemal assembly factor 5 (DNAAF5) is the transcription factor of regulating the cytoskeleton and hydrodynamic protein complex assembly, however, it was not well elucidated in the malignant progression of hepatocellular carcinoma (HCC).MethodsWe investigated the role of DNAAF5 in hepatocellular carcinoma by using multiple groups of clinical tissues combined with data from the TCGA database. Then we overexpressed DNAAF5 in hepatocellular carcinoma tumor tissues, which correlates with poor patient survival outcomes. Furthermore, we constructed stable cell lines of HCC cells to confirm the cancer-promoting effects of DNAAF5 in hepatocellular carcinoma. To explore the mechanisms of DNAAF5, transcriptome sequencing combined with mass spectrometry was also performed, which showed that DNAAF5 affects its downstream signaling pathway by interacting with PFKL and that DNAAF5 regulates PFKL protein stability by recruiting the deubiquitination protein, USP39. To corroborate these findings, the same series of tissue microarrays were used to confirm correlations between DNAAF5 and PFKL expressions. In animal experiments, DNAAF5 also promoted the proliferation of HCC cells.ResultsWe found that DNAAF5 expressions were markedly higher in HCC tissues, compared to the adjacent normal tissues. Increased levels of DNAAF5 were associated with significantly worse prognostic outcomes for HCC patients. Cell function experiments showed that HCC cells of overexpressing DNAAF5 exhibited faster proliferation rates, stronger clone formation abilities and higher drug resistance rates. However, tumor cell proliferation rates and colony formation were significantly decreased after DNAAF5 knockout, accompanied by an increase in sensitivity to sorafenib. In addition, the results of our study showed that DNAAF5 accelerates PFKL protein deubiquitination by recruiting USP39 in HCC cells. Furthermore, The overexpression of DNAAF5 could promote HCC cell proliferation in vivo and in vitro, whereas USP39 knockdown inhibited this effect. Overall, DNAAF5 serves as a scaffold protein to recruit USP39 to form a ternary complex by directly binding the PFKL protein, thereby improving the stability of the latter, which promotes the malignant process of hepatocellular carcinoma.ConclusionsThese findings revealed DNAAF5 was negatively correlated with the prognosis of patients with hepatocellular carcinoma. It underlying mechanism showed that DNAAF5 directly binds PFKL and recruits the deubiquitinated protein (USP39) to improve the stability of the PFKL protein, thus enhancing abnormal glycolysis in HCC cells.

Data-Driven Simulation of Fisher-Kolmogorov Tumor Growth Models Using Dynamic Mode Decomposition.

The computer simulation of organ-scale biomechanistic models of cancer personalized via routinely collected clinical and imaging data enables to obtain patient-specific predictions of tumor growth and treatment response over the anatomy of the patient's affected organ. These patient-specific computational forecasts have been regarded as a promising approach to personalize the clinical management of cancer and derive optimal treatment plans for individual patients, which constitute timely and critical needs in clinical oncology. However, the computer simulation of the underlying spatiotemporal models can entail a prohibitive computational cost, which constitutes a barrier to the successful development of clinically-actionable computational technologies for personalized tumor forecasting. To address this issue, here we propose to utilize dynamic-mode decomposition (DMD) to construct a low-dimensional representation of cancer models and accelerate their simulation. DMD is an unsupervised machine learning method based on the singular value decomposition that has proven useful in many applications as both a predictive and a diagnostic tool. We show that DMD may be applied to Fisher-Kolmogorov models, which constitute an established formulation to represent untreated solid tumor growth that can further accommodate other relevant cancer phenomena (e.g., therapeutic effects, mechanical deformation). Our results show that a DMD implementation of this model over a clinically relevant parameter space can yield promising predictions, with short to medium-term errors remaining under 1% and long-term errors remaining under 20%, despite very short training periods. In particular, we have found that, for moderate to high tumor cell diffusivity and low to moderate tumor cell proliferation rate, DMD reconstructions provide accurate, bounded-error reconstructions for all tested training periods. Additionally, we also show that the three-dimensional DMD reconstruction of the tumor field can be leveraged to accurately reconstruct the displacement fields of the tumor-induced deformation of the host tissue. Thus, we posit the proposed data-driven approach has the potential to greatly reduce the computational overhead of personalized simulations of cancer models, thereby facilitating tumor forecasting, parameter identification, uncertainty quantification, and treatment optimization.

Mathematical Modeling and Analysis of CD200-CD200R in Cancer Treatment.

CD200 is a cell membrane protein that binds to its receptor, CD200 receptor (CD200R). The CD200 positive tumor cells inhibit the cellular functions of M1 and M2 macrophages and dendritic cells (DCs) through the CD200-CD200R complex, resulting in downregulation of Interleukin-10 and Interleukin-12 productions and affecting the activation of cytotoxic T lymphocytes. In this work, we provide two ordinary differential equation models, one complete model and one simplified model, to investigate how the binding affinities of CD200R and the populations of M1 and M2 macrophages affect the functions of the CD200-CD200R complex in tumor growth. Our simulations demonstrate that (i) the impact of the CD200-CD200R complex on tumor promotion or inhibition highly depends on the binding affinity of the CD200R on M2 macrophages and DCs to the CD200 on tumor cells, and (ii) a stronger binding affinity of the CD200R on M1 macrophages or DCs to the CD200 on tumor cells induces a higher tumor cell density in the CD200 positive tumor. Thus, the CD200 blockade would be an efficient treatment method in this case. Moreover, the simplified model shows that the binding affinity of CD200R on macrophages is the major factor to determine the treatment efficacy of CD200 blockade when the binding affinities of CD200R on M1 and M2 macrophages are significantly different to each other. On the other hand, both the binding affinity of CD200R and the population of macrophages are the major factors to determine the treatment efficacy of CD200 blockade when the binding affinities of CD200R on M1 and M2 macrophages are close to each other. We also analyze the simplified model to investigate the dynamics of the positive and trivial equilibria of the CD200 positive tumor case and the CD200 deficient tumor case. The bifurcation diagrams show that when M1 macrophages dominate the population, the tumor cell density of the CD200 positive tumor is higher than the one of CD200 deficient tumor. Moreover, the dynamics of tumor cell density change from tumor elimination to tumor persistence to oscillation, as the maximal proliferation rate of tumor cells increases.