Genetic heterogeneity and cancer drug resistance

Combining kinase inhibitors for optimally co-targeting cancer and drug escape by exploitation of drug target promiscuities

Cancers resist targeted therapeutics by drug-escape signaling. Multitarget drugs co-targeting cancer and drug-escape mediators (DEMs) are clinically advantageous. DEM coverage may be expanded by drug combinations. This work evaluated to what extent the kinase DEMs (KDEMs) can be optimally co-targeted by drug combinations based on target promiscuities of individual drugs. We focused on 41 approved and 28 clinical trial small molecule kinase inhibitor drugs with available experimental kinome and clinical pharmacokinetic data. From the kinome inhibitory profiles of these drugs, drug combinations were assembled for optimally co-targeting an established cancer target (EGFR, HER2, ABL1, or MEK1) and 9-16 target-associated KDEMs at comparable potency levels as that against the cancer target. Each set of two-, three-, and four-drug combinations co-target 36-71%, 44-89%, 50-88%, and 27-55% KDEMs of EGFR, HER2, ABL1, and MEK1, respectively, compared with the 36, 33, 38, and 18% KDEMs maximally co-targeted by an existing drug or drug combination approved or clinically tested for the respective cancer. Some co-targeted KDEMs are not covered by any existing drug or drug combination. Our work suggested that novel drug combinations may be constructed for optimally co-targeting cancer and drug escape by the exploitation of drug target promiscuities.

Metabolic Constrains Rule Metastasis Progression

Metastasis formation accounts for the majority of tumor-associated deaths and consists of different steps, each of them being characterized by a distinctive adaptive phenotype of the cancer cells. Metabolic reprogramming represents one of the main adaptive phenotypes exploited by cancer cells during all the main steps of tumor and metastatic progression. In particular, the metabolism of cancer cells evolves profoundly through all the main phases of metastasis formation, namely the metastatic dissemination, the metastatic colonization of distant organs, the metastatic dormancy, and ultimately the outgrowth into macroscopic lesions. However, the metabolic reprogramming of metastasizing cancer cells has only recently become the subject of intense study. From a clinical point of view, the latter steps of the metastatic process are very important, because patients often undergo surgical removal of the primary tumor when cancer cells have already left the primary tumor site, even though distant metastases are not clinically detectable yet. In this scenario, to precisely elucidate if and how metabolic reprogramming drives acquisition of cancer-specific adaptive phenotypes might pave the way to new therapeutic strategies by combining chemotherapy with metabolic drugs for better cancer eradication. In this review we discuss the latest evidence that claim the importance of metabolic adaptation for cancer progression.

Organoid in colorectal cancer: progress and challenges

Patient-derived tumor organoids (PDOs) currently represent important modeling tools in pre-clinical investigation of malignancies. Organoid cultures conserve the genetic and phenotypic characteristics of the original tumor and maintain its heterogeneity, allowing their application in many research fields. PDOs derived from colorectal cancer (CRC) have been used for genetic modeling to investigate the function of driver genes. Some researchers have been exploring the value of CRC PDOs in chemotherapy, targeted therapy, and radiotherapy response prediction. The successful generation of PDOs derived from CRC could deepen our understanding of CRC biology and provide novel tools for cancer modeling, for realizing precision medicine by assessing specimens from individual patients ex vivo. The present review discusses recently reported advances in CRC PDOs and the challenges they face as pre-clinical models in CRC research.

Genotoxic and Cytotoxic Activities of Lantadene A-Loaded Gold Nanoparticles (LA-AuNPS) in MCF-7 Cell Line: An in vitro Assessment

Gold nanoparticles (AuNPs) have been widely used in many applications. Their usage as drug delivery vehicles has also gained considerable attention due to their chemical and optical properties as well as their good biocompatibility. The present study was conducted to evaluate the efficiency of AuNPs in enhancing the cytotoxic and apoptotic induction activity of lantadene A (LA), separated from Lantana camara leaves, on the breast tumor cell line MCF-7 in vitro. By utilizing plant-mediated synthesis method of nanostructures, LA-loaded AuNPs (LA-AuNPs) were prepared and their formation was confirmed by means of ultraviolet–visible spectroscope, atomic force microscope, scanning electron microscope, and zeta potential. The cytotoxic effect of LA-AuNPs was analyzed using a methylthiazol tetrazolium assay and compared to free AuNPs and LA. The results indicated a significant increase in the reduction of MCF-7 cells viability after incubation with LA-AuNPs. As determined by terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) assay, LA-AuNPs induced a greater ratio of DNA-fragmented cells compared to LA-treated and untreated cells. Also, by operating real-time polymerase chain reaction, LA-AuNPs-treated cells displayed an increased upregulation of p53 expression and downregulation of BCL-2 expression in addition to a significant reduction in the level of BCL-2-BAX ratio. No significant effect was shown on the expression of BAX. Collectively, our results indicate that LA-AuNPs showed promising cytotoxicity to MCF-7 cells as a novel nanoscale preparation, likely via induction of apoptotic genes and stimulation of DNA fragmentation.

Overcoming cancer therapeutic bottleneck by drug repurposing

Ever present hurdles for the discovery of new drugs for cancer therapy have necessitated the development of the alternative strategy of drug repurposing, the development of old drugs for new therapeutic purposes. This strategy with a cost-effective way offers a rare opportunity for the treatment of human neoplastic disease, facilitating rapid clinical translation. With an increased understanding of the hallmarks of cancer and the development of various data-driven approaches, drug repurposing further promotes the holistic productivity of drug discovery and reasonably focuses on target-defined antineoplastic compounds. The "treasure trove" of non-oncology drugs should not be ignored since they could target not only known but also hitherto unknown vulnerabilities of cancer. Indeed, different from targeted drugs, these old generic drugs, usually used in a multi-target strategy may bring benefit to patients. In this review, aiming to demonstrate the full potential of drug repurposing, we present various promising repurposed non-oncology drugs for clinical cancer management and classify these candidates into their proposed administration for either mono- or drug combination therapy. We also summarize approaches used for drug repurposing and discuss the main barriers to its uptake.

Whole Exome Sequencing of Multi-Regional Biopsies from Metastatic Lesions to Evaluate Actionable Truncal Mutations Using a Single-Pass Percutaneous Technique

We investigate the feasibility of obtaining multiple spatially-separated biopsies from a single lesion to explore intratumor heterogeneity and identify actionable truncal mutations using whole exome sequencing (WES). A single-pass radiologically-guided percutaneous technique was used to obtain four spatially-separated biopsies from a single metastatic lesion. WES was performed to identify putative truncal variants (PTVs), defined as a non-synonymous somatic (NSS) variant present in all four spatially separated biopsies. Actionable truncal mutations—filtered using the FoundationOne panel—were defined as clinically relevant PTVs. Mutational landscapes of each biopsy and their association with patient outcomes were assessed. WES on 50 biopsied samples from 13 patients across six cancer types were analyzed. Actionable truncal mutations were identified in 9/13 patients; 31.1 ± 5.12 more unique NSS variants were detected with every additional multi- region tumor biopsy (MRTB) analyzed. The number of PTVs dropped by 16.1 ± 17.9 with every additional MRTB, with the decrease most pronounced (36.8 ± 19.7) when two MRTB were analyzed compared to one. MRTB most reliably predicted PTV compared to in silico analysis of allele frequencies and cancer cell fraction based on one biopsy sample. Three patients treated with actionable truncal mutation-directed therapy derived clinical benefit. Multi-regional sampling for genomics analysis is feasible and informative to help prioritize precision-therapy strategies.

Sorafenib Resistance in Hepatocellular Carcinoma: The Relevance of Genetic Heterogeneity

Despite advances in biomedicine, the incidence and the mortality of hepatocellular carcinoma (HCC) remain high. The majority of HCC cases are diagnosed in later stages leading to the less than optimal outcome of the treatments. Molecular targeted therapy with sorafenib, a dual-target inhibitor targeting the serine-threonine kinase Raf and the tyrosine kinases VEGFR/PDGFR, is at present the main treatment for advanced-stage HCC, either in a single or combinatory regimen. However, it was observed in a large number of patients that its effectiveness is hampered by drug resistance. HCC is highly heterogeneous, within the tumor and among individuals, and this influences disease progression, classification, prognosis, and naturally cellular susceptibility to drug resistance. This review aims to provide an insight on how HCC heterogeneity influences the different primary mechanisms of chemoresistance against sorafenib including reduced drug intake, enhanced drug efflux, intracellular drug metabolism, alteration of molecular targets, activation/inactivation of signaling pathways, changes in the DNA repair machinery, and negative balance between apoptosis and survival of the cancer cells. The diverse variants, mutations, and polymorphisms in molecules and their association with drug response can be a helpful tool in treatment decision making. Accordingly, the existence of heterogeneous biomarkers in the tumor must be considered to strengthen multi-target strategies in patient-tailored treatment.

Angiogenesis in Breast Cancer Progression, Diagnosis, and Treatment

Angiogenesis is a significant event in a wide range of healthy and diseased conditions. This process frequently involves vasodilation and an increase in vascular permeability. Numerous players referred to as angiogenic factors, work in tandem to facilitate the outgrowth of endothelial cells (EC) and the consequent vascularity. Conversely, angiogenic factors could also feature in pathological conditions. Angiogenesis is a critical factor in the development of tumors and metastases in numerous cancers. An increased level of angiogenesis is associated with decreased survival in breast cancer patients. Therefore, a good understanding of the angiogenic mechanism holds a promise of providing effective treatments for breast cancer progression, thereby enhancing patients' survival. Disrupting the initiation and progression of this process by targeting angiogenic factors such as vascular endothelial growth factor (Vegf)-one of the most potent member of the VEGF family- or by targeting transcription factors, such as Hypoxia-Inducible Factors (HIFs) that act as angiogenic regulators, have been considered potential treatment options for several types of cancers. The objective of this review is to highlight the mechanism of angiogenesis in diseases, specifically its role in the progression of malignancy in breast cancer, as well as to highlight the undergoing research in the development of angiogenesis-targeting therapies.

A combinatorial strategy for overcoming primary and acquired resistance of MEK inhibition in colorectal cancer

Compared with traditional chemotherapeutic drugs, targeted therapeutic medicine has the advantages of high efficacy and less toxic side effects. However, in clinical practice for treatment of colorectal cancer, the primary and acquired resistance of these medicines limits their effectiveness in targeted therapy, therefore impedes the development of precision medicine and personalized therapy. Currently, there are limited number of drugs for targeted therapy of colorectal cancer, mainly monoclonal antibodies against EGFR or VEGFR inhibitors. Trametinib, a MEK inhibitor, has been applied in melanoma patient successfully, but not been used in clinical treatment of colorectal cancer because of its drug resistance. To identify the resistance mechanism of colorectal cancer cells to trametinib and find useful chemical combination to overcome the resistance, we screened primary and acquired cell line first and then tested multiple synergistic drug combinations by using the Chou-Talalay method. We obtained the primary resistant cell lines SW480, CW-2 and the acquired drug-resistant cell line RKO-R as well as a synergistic combination of trametinib and GSK2126458. This combination inhibits the colony formation of colorectal cancer cells and the growth of xenograft tumors in nude mice. Mechanistic analysis showed that trametinib can activate the alternative PI3K-AKT signaling pathway while inhibiting the MAPK pathway, which may be one of the molecular mechanisms of primary and acquired trametinib tolerance in colorectal cancer cells. Importantly, this bypass activation can be blocked by GSK2126458. These results suggest that a combination of trametinib and GSK2126458 is an effective approach for treating colorectal cancer resistance to trametinib.

A synopsis of prostate organoid methodologies, applications, and limitations

BACKGROUND

Current in vitro modeling systems do not fully reflect the biologic and clinical diversity of prostate cancer (PCa). Organoids are 3D in vitro cell cultures that recapitulate disease heterogeneity, retain prostate gland architecture, and mirror parental tumor characteristics.

METHODS

To make better use of organoid models in the PCa research field, we provide a review of cutting-edge prostate organoid methodologies, applications, and limitations.

RESULTS

We summarize methodologies for the establishment of benign prostate and PCa organoids and describe some of the model's practical applications and challenges. We highlight the patient-derived xenograft (PDX)-organoid interface model, which may allow for the generation of organoids from primary and rare PCa subtypes. Finally, we discuss potential future utilizations of PCa organoids in the realms of drug development and precision oncology.

CONCLUSIONS AND FUTURE DIRECTIONS

Organoids represent a quasi in vivo modeling system that can be easily amenable to genetic modification and functional studies. As such, organoids may serve as an intermediate preclinical model for studying PCa. Future directions may include the refinement of culturing conditions to increase drug response fidelity in PCa organoids. The PDX-organoid interface model may enable the future establishment of primary and rare subtype PCa organoid lines.

Comprehensive Cancer Panel Sequencing Defines Genetic Diversity and Changes in the Mutational Characteristics of Pancreatic Cancer Patients Receiving Neoadjuvant Treatment

Background/Aims

Pancreatic ductal adenocarcinoma (PDA) is associated with an extremely poor prognosis. This study assessed the genetic diversity among patients with PDA and compared their mutational profiles before and after treatment.

Methods

Tumors and matched blood samples were obtained from 22 PDA patients treated with neoadjuvant chemoradiation therapy. The somatic mutations were analyzed with comprehensive cancer gene panel (CCP). In addition, the biopsy samples obtained at diagnosis and the surgically resected samples after treatment were compared for seven patients. The CCP provided formalin-fixed paraffin-embedded sample-compatible multiplexed target selection for 409 genes implicated in cancer.

Results

Assessments of the MLH1, MLH3, MSH2, and PMS2 genes showed that the four patients with the highest relative burdens of mutations harbored somatic mutations in at least three of these genes. Genes in the histone-lysine N-methyltransferase 2 (KMT2) family, such as KMT2D, KMT2A, and KMT2C, were frequently mutated in tumor samples. Survival was worse in patients with ARID1A gene mutations than those without ARID1A gene mutations. Mutation patterns were compared between tissue samples before and after neoadjuvant treatment in seven patients who underwent surgical resection. The allelic fraction of mutations in KRAS codon 12 was lower in the surgically resected samples than in the endoscopic ultrasonography-guided fine needle aspiration biopsy samples of six patients. The number of mutant alleles of the histone lysine methyltransferase gene WHSC1 also decreased after treatment.

Conclusions

These results indicate that tumor tissue from PDA patients is genetically diverse and suggest that ARID1A mutations may be a potential prognostic marker for PDA.

HDAC inhibition synergizes with ALK inhibitors to overcome resistance in a novel ALK mutated lung adenocarcinoma model

OBJECTIVES

Somatic chromosomal rearrangements resulting in ALK fusion oncogenes are observed in 3-7 % of lung adenocarcinomas. ALK tyrosine kinase inhibitors (ALKi) induce initially response, however, various resistance mechanisms limit their efficacy. Novel therapeutic approaches are of utmost importance to tailor these targeted therapies.

MATERIALS AND METHODS

A synchronous ALK-rearranged and mutated lung cancer cell line pair was established from malignant pleural effusion (PF240-PE) and carcinosis (PF240-PC) at time of ALKi resistance. Immunohistochemistry, FISH and sequencing were performed in pre- and post-treatment tumors and in both cell lines. Differentiation markers were measured by immunoblot. Viability was tested following treatment with ALKi and/or a pan-HDAC inhibitor. Additionally, a novel treatment-naïve ALK-rearranged cell line served as control. In vivo tumorigenicity was evaluated in subcutaneous xenografts.

RESULTS

Two distinct resistance mutations were identified in different carcinosis tissues at time of resistance, the previously described resistance mutation L1152R and the hitherto uncharacterized E1161K. Strikingly, PF240-PC cells carried E1161K and PF240-PE cells harbored L1152R. Immunohistochemistry and immunoblot identified epithelial-to-mesenchymal transition markers upregulated following ALKi resistance development both in carcinosis tissues and cell lines. While both lines grew as xenografts, they differed in morphology, migration, in vivo growth and sensitivity to ALKi in vitro. Strikingly, the combination of ALKi with SAHA yielded strong synergism.

CONCLUSION

Using a patient-derived ALKi resistant lung cancer model we demonstrated the synergism of HDAC and ALK inhibition. Furthermore, our findings provide strong evidence for intratumoral heterogeneity under targeted therapy and highlight the importance of site-specific mutational analysis.

Tumor-Oriented Telomerase-Terminated Nanoplatform as Versatile Strategy for Multidrug Resistance Reversal in Cancer Treatment

Multidrug resistance is one of the major problems in chemotherapy, and exploiting impactful targets to reverse drug resistance of most tumors remains a difficult problem. In this study, the tumor-oriented nanoparticle, BIBR1532-loaded peptide dendrimeric prodrug nanoassembly (B-PDPN), is used to assist telomerase inhibition for multidrug resistance reversal. B-PDPN possesses the characteristics of an acid-activated histidine to promote cellular uptake, a redox-sensitive poly(ethylene glycol) (PEG) layer to actualize endosomal escape and telomerase inhibitor release, and an acid sensitive chemical bond to facilitate chemotherapeutic drug release. Telomerase termination weakens the protective effect of hTERT protein on mitochondria and enhances reactive oxygen species (ROS) production, which increases DNA damage and apoptosis. The tumor-oriented nanoparticle B-PDPN achieves a broad-spectrum telomerase inhibition to combat multidrug resistance. In vivo experiments support the evidence that B-PDPN accumulates in the tumor site and reduces the expression of hTERT in tumor tissues to inhibit drug resistant tumor growth. This work introduces an innovative strategy of utilizing features of tumor-activated nanoplatform to assist telomerase termination. The nanoplatform enhances intracellular drug concentration and nucleus delivery of doxorubicin (DOX), and promotes DNA damage to combat multidrug resistance.

Gene regulatory network analysis with drug sensitivity reveals synergistic effects of combinatory chemotherapy in gastric cancer

The combination of docetaxel, cisplatin, and fluorouracil (DCF) is highly synergistic in advanced gastric cancer. We aimed to explain these synergistic effects at the molecular level. Thus, we constructed a weighted correlation network using the differentially expressed genes between Stage I and IV gastric cancer based on The Cancer Genome Atlas (TCGA), and three modules were derived. Next, we investigated the correlation between the eigengene of the expression of the gene network modules and the chemotherapeutic drug response to DCF from the Genomics of Drug Sensitivity in Cancer (GDSC) database. The three modules were associated with functions related to cell migration, angiogenesis, and the immune response. The eigengenes of the three modules had a high correlation with DCF (−0.41, −0.40, and −0.15). The eigengenes of the three modules tended to increase as the stage increased. Advanced gastric cancer was affected by the interaction the among modules with three functions, namely cell migration, angiogenesis, and the immune response, all of which are related to metastasis. The weighted correlation network analysis model proved the complementary effects of DCF at the molecular level and thus, could be used as a unique methodology to determine the optimal combination of chemotherapy drugs for patients with gastric cancer.

The impact of new systemic therapies on survival and time on hormonal treatment in hormone receptor-positive, human epidermal growth factor receptor 2-negative metastatic breast cancer: A population-based study in British Columbia from 2003 to 2013

BACKGROUND

The purpose of this study was to determine whether new systemic therapy regimens have resulted in improved survival and increased time on first- and second-line hormonal treatment for patients with hormone receptor (HR)-positive metastatic breast cancer (MBC) over time.

METHODS

Patients diagnosed with HR-positive, human epidermal growth factor receptor 2 (HER2)-negative MBC were identified across 3 time cohorts (2003-2005, 2007-2009, and 2011-2013). Data were prospectively collected. Cases with previous, synchronous, or subsequent contralateral breast cancer were excluded. The types of first- and second-line therapies, the times on first- and second-line hormonal treatment, and the median survival times were compared across the cohorts.

RESULTS

Within the time period analyzed, 9 new adjuvant systemic therapies (with or without neoadjuvant therapy) and 2 metastatic systemic therapies were approved at BC Cancer for the treatment of HR-positive, HER2-negative MBC. In the 3 time cohorts, 3953 patients diagnosed with MBC were identified. Among the 2432 patients (62%) who had HR-positive/HER2-negative disease, 2197 (90%) received at least 1 line of systemic therapy after the diagnosis of MBC, and 80% of these patients (1752 of 2197) received first- and/or second-line hormonal treatment. The median duration on hormonal treatment was 9.0 months for the first line and 6.1 months for the second line. The durations were similar across the time cohorts (range for the first line, 8.9-9.0 months; range for the second line, 6.0-6.1 months). The median survival for the entire study population was 2.0 years (95% confidence interval, 1.8-2.1 years), and there was no significant difference between the cohorts (range, 1.9-2.0 years).

CONCLUSIONS

Even though more adjuvant and metastatic systemic therapies have been approved since 2003, population-level gains in survival and the time on hormonal treatment for patients with HR-positive, HER2-negative MBC have not been made over the course of a decade.

Both BRCA1-wild type and -mutant triple-negative breast cancers show sensitivity to the NAE inhibitor MLN4924 which is enhanced upon MLN4924 and cisplatin combination treatment

Triple-negative breast cancer (TNBC) shows limited therapeutic efficacy. PARP inhibitor has been approved to treat advanced BRCA-mutant breast cancer but shows high resistance. Therefore, the development of new therapeutics that sensitize TNBC irrespective of BRCA status is urgently needed. The neddylation pathway plays a critical role in many physiological processes by regulating the degradation of proteins. MLN4924, a selective inhibitor of the key neddylation enzyme NEDD8 Activation Enzyme (NAE1), shows higher sensitivity to both BRCA1-wild type and -mutant TNBCs compared to other breast cancer subtypes. MLN4924 induced re-replication with >4N DNA content leading to robust DNA damage. Accumulation of unrepaired DNA damage resulted in S and G2/M arrest causing apoptosis and senescence, due to the stabilization of the replication initiation protein CDT1 and the accumulation of cell cycle proteins upon MLN4924 treatment. Moreover, adding MLN4924 to the standard TNBC chemotherapeutic agent cisplatin increased the DNA damage level, further enhancing the sensitivity. In vivo, MLN4924 reduced tumor growth in a NOD-SCID mouse xenograft model by inducing DNA damage which was further augmented with the MLN4924 and cisplatin cotreatment. NAE1 is overexpressed in TNBC cell lines and in patients compared to other breast cancer subtypes suggesting that NAE1 status is prognostic of MLN4924 treatment response and outcome. Taken together, we demonstrated the mechanism of TNBC sensitization by the MLN4924 and MLN4924/cisplatin treatments irrespective of BRCA1 status, provided a strong justification for using MLN4924 alone or in combination with cisplatin, and identified a genetic background in which this combination will be particularly effective.

Immersion Bioprinting of Tumor Organoids in Multi-Well Plates for Increasing Chemotherapy Screening Throughput

The current drug development pipeline takes approximately fifteen years and $2.6 billion to get a new drug to market. Typically, drugs are tested on two-dimensional (2D) cell cultures and animal models to estimate their efficacy before reaching human trials. However, these models are often not representative of the human body. The 2D culture changes the morphology and physiology of cells, and animal models often have a vastly different anatomy and physiology than humans. The use of bioengineered human cell-based organoids may increase the probability of success during human trials by providing human-specific preclinical data. They could also be deployed for personalized medicine diagnostics to optimize therapies in diseases such as cancer. However, one limitation in employing organoids in drug screening has been the difficulty in creating large numbers of homogeneous organoids in form factors compatible with high-throughput screening (e.g., 96- and 384-well plates). Bioprinting can be used to scale up deposition of such organoids and tissue constructs. Unfortunately, it has been challenging to 3D print hydrogel bioinks into small-sized wells due to well-bioink interactions that can result in bioinks spreading out and wetting the well surface instead of maintaining a spherical form. Here, we demonstrate an immersion printing technique to bioprint tissue organoids in 96-well plates to increase the throughput of 3D drug screening. A hydrogel bioink comprised of hyaluronic acid and collagen is bioprinted into a viscous gelatin bath, which blocks the bioink from interacting with the well walls and provides support to maintain a spherical form. This method was validated using several cancerous cell lines, and then applied to patient-derived glioblastoma (GBM) and sarcoma biospecimens for drug screening.

Intratumoral Genetic Heterogeneity in Papillary Thyroid Cancer: Occurrence and Clinical Significance

Intratumoral heterogeneity (ITH) refers to a subclonal genetic diversity observed within a tumor. ITH is the consequence of genetic instability and accumulation of genetic alterations, two mechanisms involved in the progression from an early tumor stage to a more aggressive cancer. While this process is widely accepted, the ITH of early stage papillary thyroid carcinoma (PTC) is debated. By different genetic analysis, several authors reported the frequent occurrence of PTCs composed of both tumor cells with and without RET/PTC or BRAF^V600E genetic alterations. While these data, and the report of discrepancies in the genetic pattern between metastases and the primary tumor, demonstrate the existence of ITH in PTC, its extension and biological significance is debated. The ITH takes on a great significance when involves oncogenes, such as RET rearrangements and BRAF^V600E as it calls into question their role of driver genes. ITH is also predicted to play a major clinical role as it could have a significant impact on prognosis and on the response to targeted therapy. In this review, we analyzed several data indicating that ITH is not a marginal event, occurring in PTC at any step of development, and suggesting the existence of unknown genetic or epigenetic alterations that still need to be identified.

In Silico implementation of evolutionary paradigm in therapy design: Towards anti-cancer therapy as Darwinian process

In here presented in silico study we suggest a way how to implement the evolutionary principles into anti-cancer therapy design. We hypothesize that instead of its ongoing supervised adaptation, the therapy may be constructed as a self-sustaining evolutionary process in a dynamic fitness landscape established implicitly by evolving cancer cells, microenvironment and the therapy itself. For these purposes, we replace a unified therapy with the 'therapy species', which is a population of heterogeneous elementary therapies, and propose a way how to turn the toxicity of the elementary therapy into its fitness in a way conforming to evolutionary causation. As a result, not only the therapies govern the evolution of different cell phenotypes, but the cells' resistances govern the evolution of the therapies as well. We illustrate the approach by the minimalistic ad hoc evolutionary model. Its results indicate that the resistant cells could bias the evolution towards more toxic elementary therapies by inhibiting the less toxic ones. As the evolutionary causation of cancer drug resistance has been intensively studied for a few decades, we refer to cancer as a special case to illustrate purely theoretical analysis.

Latency and interval therapy affect the evolution in metastatic colorectal cancer

While comparison of primary tumor and metastases has highlighted genomic heterogeneity in colorectal cancer (CRC), previous studies have focused on a single metastatic site or limited genomic testing. Combining data from whole exome and ultra-deep targeted sequencing, we explored possible evolutionary trajectories beyond the status of these mutations, particularly among patient-matched metastatic tumors. Our findings confirm the persistence of known clinically-relevant mutations (e.g., those of RAS family of oncogenes) in CRC primary and metastases, yet reveal that latency and interval systemic therapy affect the course of evolutionary events within metastatic lesions. Specifically, our analysis of patient-matched primary and multiple metastatic lesions, developed over time, showed a similar genetic composition for liver metastatic tumors, which were 21-months apart. This genetic makeup was different from those identified in lung metastases developed before manifestation of the second liver metastasis. These results underscore the role of latency in the evolutionary path of metastatic CRC and may have implications for future treatment options.

Diversity of collective migration patterns of invasive breast cancer cells emerging during microtrack invasion

Understanding the mechanisms underlying the diversity of tumor invasion dynamics, including single-cell migration, multicellular streaming, and the emergence of various collective migration patterns, is a long-standing problem in cancer research. Here we have designed and fabricated a series of microchips containing high-throughput microscale tracks using protein repelling coating technology, which were then covered with a thin Matrigel layer. By varying the geometrical confinement (track width) and microenvironment factors (Matrigel concentration), we have reproduced a diversity of collective migration patterns in the chips, which were also observed in vivo. We have further classified the collective patterns and quantified the emergence probability of each class of patterns as a function of microtrack width and Matrigel concentration to devise a quantitive "collective pattern diagram." To elucidate the mechanisms behind the emergence of various collective patterns, we employed cellular automaton simulations, incorporating the effects of both direct cell-cell interactions and microenvironment factors (e.g., chemical gradient and extracellular matrix degradation). Our simulations suggest that tumor cell phenotype heterogeneity, and the associated dynamic selection of a favorable phenotype via cell-microenivronment interactions, are key to the emergence of the observed collective patterns in vitro.

Reliability of Whole-Exome Sequencing for Assessing Intratumor Genetic Heterogeneity

Multi-region sequencing is used to detect intratumor genetic heterogeneity (ITGH) in tumors. To assess whether genuine ITGH can be distinguished from sequencing artifacts, we performed whole-exome sequencing (WES) on three anatomically distinct regions of the same tumor with technical replicates to estimate technical noise. Somatic variants were detected with three different WES pipelines and subsequently validated by high-depth amplicon sequencing. The cancer-only pipeline was unreliable, with about 69% of the identified somatic variants being false positive. Even with matched normal DNA for which 82% of the somatic variants were detected reliably, only 36%-78% were found consistently in technical replicate pairs. Overall, 34%-80% of the discordant somatic variants, which could be interpreted as ITGH, were found to constitute technical noise. Excluding mutations affecting low-mappability regions or occurring in certain mutational contexts was found to reduce artifacts, yet detection of subclonal mutations by WES in the absence of orthogonal validation remains unreliable.

What can artificial intelligence teach us about the molecular mechanisms underlying disease?

While molecular imaging with positron emission tomography or single-photon emission computed tomography already reports on tumour molecular mechanisms on a macroscopic scale, there is increasing evidence that there are multiple additional features within medical images that can further improve tumour characterization, treatment prediction and prognostication. Early reports have already revealed the power of radiomics to personalize and improve patient management and outcomes. What remains unclear is how these additional metrics relate to underlying molecular mechanisms of disease. Furthermore, the ability to deal with increasingly large amounts of data from medical images and beyond in a rapid, reproducible and transparent manner is essential for future clinical practice. Here, artificial intelligence (AI) may have an impact. AI encompasses a broad range of 'intelligent' functions performed by computers, including language processing, knowledge representation, problem solving and planning. While rule-based algorithms, e.g. computer-aided diagnosis, have been in use for medical imaging since the 1990s, the resurgent interest in AI is related to improvements in computing power and advances in machine learning (ML). In this review we consider why molecular and cellular processes are of interest and which processes have already been exposed to AI and ML methods as reported in the literature. Non-small-cell lung cancer is used as an exemplar and the focus of this review as the most common tumour type in which AI and ML approaches have been tested and to illustrate some of the concepts.

Predominance of M2 macrophages in gliomas leads to the suppression of local and systemic immunity

Glioblastoma is a highly prevalent and aggressive form of primary brain tumor. It represents approximately 56% of all the newly diagnosed gliomas. Macrophages are one of the major constituents of tumor-infiltrating immune cells in the human gliomas. The role of immunosuppressive macrophages is very well documented in correlation with the poor prognosis of patients suffering from breast, prostate, bladder and cervical cancers. The current study highlights the correlation between the tumor-associated macrophage phenotypes and glioma progression. We observed an increase in the pool of M2 macrophages in high-grade gliomas, as confirmed by their CD68 and CD163 double-positive phenotype. In contrast, less M1 macrophages were noticed in high-grade gliomas, as evidenced by the down-regulation in the expression of CCL3 marker. In addition, we observed that higher gene expression ratio of CD163/CCL3 is associated with glioma progression. The Kaplan-Meier survival plots indicate that glioma patients with lower expression of M2c marker (CD163), and higher expression of M1 marker (CCL3) had better survival. Furthermore, we examined the systemic immune response in the peripheral blood and noted a predominance of M2 macrophages, myeloid-derived suppressor cells and PD-1⁺ CD4 T cells in glioma patients. Thus, the study indicates a high gene expression ratio of CD163/CCL3 in high-grade gliomas as compared to low-grade gliomas and significantly elevated frequency of M2 macrophages and PD-1⁺ CD4 T cells in the blood of tumor patients. These parameters could be used as an indicator of the early diagnosis and prognosis of the disease.

Identification of pharmacodynamic biomarkers and common molecular mechanisms of response to genotoxic agents in cancer cell lines

PURPOSE

Genotoxic agents (GAs) including cisplatin, doxorubicin, gemcitabine, and topotecan are often used in cancer treatment. However, the response to GAs is variable among patients and predictive biomarkers are inadequate to select patients for treatment. Accurate and rapid pharmacodynamics measures of response can, thus, be useful for monitoring therapy and improve clinical outcomes.

METHODS

This study focuses on integrating a database of genome-wide response to treatment (The NCI Transcriptional Pharmacodynamics Workbench) with a database of baseline gene expression (GSE32474) for the NCI-60 cell lines to identify mechanisms of response and pharmacodynamic (PD) biomarkers.

RESULTS AND CONCLUSIONS

Our analysis suggests that GA-induced endoplasmic reticulum (ER) stress may signal for GA-induced cell death. Reducing the uptake of GA, activating DNA repair, and blocking ER-stress induction cooperate to prevent GA-induced cell death in the GA-resistant cells. ATF3, DDIT3, CARS, and PPP1R15A appear as possible candidate PD biomarkers for monitoring the progress of GA treatment. Further validation studies on the proposed intrinsic drug-resistant mechanism and candidate genes are needed using in vivo data from either patient-derived xenograft models or clinical chemotherapy trials.

Modeling genetic heterogeneity of drug response and resistance in cancer

Heterogeneity in tumors is recognized as a key contributor to drug resistance and spread of advanced disease, but deep characterization of genetic variation within tumors has only recently been quantifiable with the advancement of next generation sequencing and single cell technologies. These data have been essential in developing molecular models of how tumors develop, evolve, and respond to environmental changes, such as therapeutic intervention. A deeper understanding of tumor evolution has subsequently opened up new research efforts to develop mathematical models that account for evolutionary dynamics with the goal of predicting drug response and resistance in cancer. Here, we describe recent advances and limitations of how models of tumor evolution can impact treatment strategies for cancer patients.

Induction of Mitochondrial Cell Death and Reversal of Anticancer Drug Resistance via Nanocarriers Composed of a Triphenylphosphonium Derivative of Tocopheryl Polyethylene Glycol Succinate

We have devised a nanocarrier using "tocopheryl polyethylene glycol succinate (TPGS) conjugated to triphenylphosphonium cation" (TPP-TPGS) for improving the efficacy of doxorubicin hydrochloride (DOX). Triphenylphosphonium cation (TPP) has affinity for an elevated transmembrane potential gradient (mitochondrial), which is usually high in cancer cells. Consequently, when tested in molecular docking and cytotoxicity assays, TPP-TPGS, owing to its structural similarity to mitochondrially directed anticancer compounds of the "tocopheryl succinate" family, interferes specifically in mitochondrial CII enzyme activity, increases intracellular oxidative stress, and induces apoptosis in breast cancer cells. DOX loaded nanocarrier (DTPP-TPGS) constructed using TPP-TPGS was positively charged, spherical in shape, sized below 100 nm, and had its drug content distributed evenly. DTPP-TPGS offers greater intracellular drug delivery due to its rapid endocytosis and subsequent endosomal escape. DTPP-TPGS also efficiently inhibits efflux transporter P glycoprotein (PgP), which, along with greater cell uptake and inherent cytotoxic activity of the construction material (TPP-TPGS), cumulatively results in 3-fold increment in anticancer activity of DOX in resistant breast cancer cells as well as greater induction of necroapoptosis and arrest in all phases of the cell cycle. DTPP-TPGS after intravenous administration in Balb/C mice with breast cancer accumulates preferentially in tumor tissue, which produces significantly greater antitumor activity when compared to DOX solution. Toxicity evaluation was also performed to confirm the safety of this formulation. Overall TPP-TPGS is a promising candidate for delivery of DOX.

Uncovering the Genomic Landscape in Newly Diagnosed and Relapsed Pediatric Cytogenetically Normal FLT3-ITD AML

Fms-like tyrosine kinase 3 (FLT3) internal tandem duplication (ITD) mutations, common in pediatric acute myeloid leukemia (AML), associate with early relapse and poor prognosis. Past studies have suggested additional cooperative mutations are required for leukemogenesis in FLT3-ITD+ AML. Using RNA sequencing and a next-generation targeted gene panel, we broadly characterize the co-occurring genomic alterations in pediatric cytogenetically normal (CN) FLT3-ITD+ AML to gain a deeper understanding of the clonal patterns and heterogeneity at diagnosis and relapse. We show that chimeric transcripts were present in 21 of 34 (62%) of de novo samples, 2 (6%) of these samples included a rare reoccurring fusion partner BCL11B. At diagnosis, the median number of mutations other than FLT3 per patient was 1 (range 0-3), which involved 8 gene pathways; WT1 and NPM1 mutations were frequently observed (35% and 24%, respectively). Fusion transcripts and high variant allele frequency (VAF) mutants, which included WT1, NPM1, SMARCA2, RAD21, and TYK2, were retained from diagnosis to relapse. We did observe reduction in VAF of simple or single mutation clones, but VAFs were preserved or expanded in more complex clones with multiple mutations. Our data provide the first insight into the genomic complexity of pediatric CN FLT3-ITD+ AML and could help stratify future targeted treatment strategies.

Assessment of spatial tumor heterogeneity using CT growth patterns estimated by tumor tracking on 3D CT volumetry of multiple pulmonary metastatic nodules

Purpose

Our purpose was to assess the differences in growth rates of multiple pulmonary metastatic nodules using three-dimensional (3D) computed tomography (CT) volumetry and propose a concept of CT spatial tumor heterogeneity.

Materials and methods

We manually measured the largest diameter of metastatic pulmonary nodules on chest CT scans, and calculated the 3D maximum diameter and the volume using a semi-automated 3D CT volumetry of each nodule. The tumor response was assessed according to the revised RECIST 1.1. We defined a nodule as an outlier based on 1.5 times growth during follow-up. The CT spatial tumor heterogeneity was statistically analyzed by the “minimum combination t-test method” devised in our study.

Results

On manual measurement, the tumor response category was stable disease (SD) in all 10 patients. Of them, total 155 metastatic nodules (4–52 nodules per patient) were segmented using the 3D CT volumetry. In the 3D maximum diameter, 9 patients had SD except for one patient with partial response in the two selected nodules; for the volume, all 10 patients were SD. For the 3D maximum diameter, six patients had at least one outlier; whereas five patients had the outlier on the volume measurement. Six patients were proven to have overall CT spatial tumor heterogeneity.

Conclusions

The spatial tumor heterogeneity determined in a CT parametric approach could be statistically assessed. In patients with CT spatial heterogeneity, tumors with different growth rates may be neglected when the nodules are assessed according to the current guideline.

Electric charge conversable drug liposomes enable to enhance treatment efficacy of breast cancer

Intrinsic drug resistance has been demonstrated in different types of breast cancer cells, leading to the recurrence of disease after treatment. Here, we report a functional drug liposome that enables electric charge conversion in the weak acidic milieu of cancer to enhance the treatment efficacy of different breast cancers. The functional drug liposomes were developed by encapsulating daunorubicin and rofecoxib, and modified with new functional material, D-alpha tocopherol acid succinate-polyethylene glycol-glutarate (TPGS1000-glutarate). The results demonstrated that the liposomes promoted the effects of cellular uptake and lysosomal escape, followed by targeting the mitochondria. Consequently, the electric charge conversable drug liposomes significantly enhanced the treatment efficacy by initiating a cascade of reactions through inducing autophagy and apoptosis in different breast cancer cells. In conclusion, the electric charge conversable drug liposomes enable to enhance treatment efficacy of different breast cancers, and hence the study could offer a broadly applicable strategy to enhance efficacy against heterogeneous and refractory cancer cells.

Genomic Profiling of Blood-Derived Circulating Tumor DNA from Patients with Colorectal Cancer: Implications for Response and Resistance to Targeted Therapeutics

Molecular profiling of circulating tumor DNA (ctDNA) is a promising noninvasive tool. Here, next-generation sequencing (NGS) of blood-derived ctDNA was performed in patients with advanced colorectal cancer. We investigated ctDNA-derived genomic alterations, including potential actionability, concordance with tissue NGS, and serial dynamics in 78 patients with colorectal cancer using a clinical-grade NGS assay that detects single nucleotide variants (54-73 genes) and selected copy-number variants, fusions, and indels. Overall, 63 patients [80.8% (63/78)] harbored ctDNA alterations; 59 [75.6% (59/78)], ≥1 characterized alteration (variants of unknown significance excluded). All 59 patients had actionable alterations potentially targetable with FDA-approved drugs [on-label and/or off-label (N = 54) or with experimental drugs in clinical trials (additional five patients); University of California San Diego Molecular Tumor Board assessment]: 45, by OncoKB (http://oncokb.org/#/). The tissue and blood concordance rates for common specific alterations ranged from 62.3% to 86.9% (median = 5 months between tests). In serial samples from patients on anti-EGFR therapy, multiple emerging alterations in genes known to be involved in therapeutic resistance, including KRAS, NRAS, BRAF, EGFR, ERBB2, and MET were detected. In conclusion, over 80% of patients with stage IV colorectal cancer had detectable ctDNA, and the majority had potentially actionable alterations. Concordance between tissue and blood was between 62% and 87%, despite a median of 5 months between tests. Resistance alterations emerged on anti-EGFR therapy. Therefore, biopsy-free, noninvasive ctDNA analysis provides data relevant to the clinical setting. Importantly, sequential ctDNA analysis detects patterns of emerging resistance allowing for precision planning of future therapy.

Assessment of intratumoral heterogeneity with mutations and gene expression profiles

Intratumoral heterogeneity (ITH) refers to the presence of distinct tumor cell populations. It provides vital information for the clinical prognosis, drug responsiveness, and personalized treatment of cancer patients. As genomic ITH in various cancers affects the expression patterns of genes, the expression profile could be utilized for determining ITH level. Herein, we present a novel approach to directly detect high ITH defined as a larger number of subclones from the gene expression pattern through machine learning approaches. We examined associations between gene expression profile and ITH of 12 cancer types from The Cancer Genome Atlas (TCGA) database. Using stomach adenocarcinoma (STAD) showing high association, we evaluated the performance of our method in predicting ITH by employing three machine learning algorithms using gene expression profile data. We classified tumors into high and low heterogeneity groups using the learning model through the selection of LASSO feature. The result showed that support vector machines (SVMs) outperformed other algorithms (AUC = 0.84 in SVMs and 0.82 in Naïve Bayes) and we were able to improve predictive power by using both combined data from mutation and expression. Furthermore, we evaluated the prediction ability of each model using simulation data generated by mixing cell lines of the Cancer Cell Line Encyclopedia (CCLE), and obtained consistent results with using real dataset. Our approach could be utilized for discriminating tumors with heterogeneous cell populations to characterize ITH.

Intrinsic resistance to EGFR-Tyrosine Kinase Inhibitors in EGFR-Mutant Non-Small Cell Lung Cancer: Differences and Similarities with Acquired Resistance

Activating mutations in the epidermal growth factor receptor gene occur as early cancer-driving clonal events in a subset of patients with non-small cell lung cancer (NSCLC) and result in increased sensitivity to EGFR-tyrosine-kinase-inhibitors (EGFR-TKIs). Despite very frequent and often prolonged clinical response to EGFR-TKIs, virtually all advanced EGFR-mutated (EGFRM+) NSCLCs inevitably acquire resistance mechanisms and progress at some point during treatment. Additionally, 20-30% of patients do not respond or respond for a very short time (<3 months) because of intrinsic resistance. While several mechanisms of acquired EGFR-TKI-resistance have been determined by analyzing tumor specimens obtained at disease progression, the factors causing intrinsic TKI-resistance are less understood. However, recent comprehensive molecular-pathological profiling of advanced EGFRM+ NSCLC at baseline has illustrated the co-existence of multiple genetic, phenotypic, and functional mechanisms that may contribute to tumor progression and cause intrinsic TKI-resistance. Several of these mechanisms have been further corroborated by preclinical experiments. Intrinsic resistance can be caused by mechanisms inherent in EGFR or by EGFR-independent processes, including genetic, phenotypic or functional tumor changes. This comprehensive review describes the identified mechanisms connected with intrinsic EGFR-TKI-resistance and differences and similarities with acquired resistance and among clinically implemented EGFR-TKIs of different generations. Additionally, the review highlights the need for extensive pre-treatment molecular profiling of advanced NSCLC for identifying inherently TKI-resistant cases and designing potential combinatorial targeted strategies to treat them.

Shared Molecular Targets Confer Resistance over Short and Long Evolutionary Timescales

Pre-existing and de novo genetic variants can both drive adaptation to environmental changes, but their relative contributions and interplay remain poorly understood. Here we investigated the evolutionary dynamics in drug-treated yeast populations with different levels of pre-existing variation by experimental evolution coupled with time-resolved sequencing and phenotyping. We found a doubling of pre-existing variation alone boosts the adaptation by 64.1% and 51.5% in hydroxyurea and rapamycin, respectively. The causative pre-existing and de novo variants were selected on shared targets: RNR4 in hydroxyurea and TOR1, TOR2 in rapamycin. Interestingly, the pre-existing and de novo TOR variants map to different functional domains and act via distinct mechanisms. The pre-existing TOR variants from two domesticated strains exhibited opposite rapamycin resistance effects, reflecting lineage-specific functional divergence. This study provides a dynamic view on how pre-existing and de novo variants interactively drive adaptation and deepens our understanding of clonally evolving populations.

Interplay of Darwinian Selection, Lamarckian Induction and Microvesicle Transfer on Drug Resistance in Cancer

Development of drug resistance in cancer has major implications for patients’ outcome. It is related to processes involved in the decrease of drug efficacy, which are strongly influenced by intratumor heterogeneity and changes in the microenvironment. Heterogeneity arises, to a large extent, from genetic mutations analogously to Darwinian evolution, when selection of tumor cells results from the adaptation to the microenvironment, but could also emerge as a consequence of epigenetic mutations driven by stochastic events. An important exogenous source of alterations is the action of chemotherapeutic agents, which not only affects the signalling pathways but also the interactions among cells. In this work we provide experimental evidence from in vitro assays and put forward a mathematical kinetic transport model to describe the dynamics displayed by a system of non-small-cell lung carcinoma cells (NCI-H460) which, depending on the effect of a chemotherapeutic agent (doxorubicin), exhibits a complex interplay between Darwinian selection, Lamarckian induction and the nonlocal transfer of extracellular microvesicles. The role played by all of these processes to multidrug resistance in cancer is elucidated and quantified.

Co-delivery of D-(KLAKLAK)2 Peptide and Chlorin e6 using a Liposomal Complex for Synergistic Cancer Therapy

Nanotechnology-based photo-chemo combination therapy has been extensively investigated to improve therapeutic outcomes in anticancer treatment. Specifically, with the help of a singlet oxygen generated by the photosensitizer, the endocytosed nanoparticles are allowed to escape from the endosomal compartment, which is currently an obstacle in nanotechnology-based anticancer therapy. In this study, a liposomal complex system (Lipo (Pep, Ce6)), composed of a chlorin e6-conjugated di-block copolymer (PEG-PLL(-g-Ce6)) and a D-(KLAKLAK)2 peptide loading liposome (Lipo (Pep)), was developed and evaluated for its anticancer activity. Due to the membrane lytic ability of the D-(KLAKLAK)2 peptide and the membrane disruptive effect of the singlet oxygen generated from chlorin e6, Lipo (Pep, Ce6) accelerated the disruption of the endosomal compartment, and exhibited strong synergistic anticancer activity in vitro. The prepared liposomal complex system could potentially maximize the efficacy of the nanotechnology-based photo-chemo combination therapy, and can be regarded as a novel, versatile strategy in advanced tumor therapy.

Drug resistance and combating drug resistance in cancer

Cancer is the second leading cause of death in the US. Current major treatments for cancer management include surgery, cytotoxic chemotherapy, targeted therapy, radiation therapy, endocrine therapy and immunotherapy. Despite the endeavors and achievements made in treating cancers during the past decades, resistance to classical chemotherapeutic agents and/or novel targeted drugs continues to be a major problem in cancer therapies. Drug resistance, either existing before treatment (intrinsic) or generated after therapy (acquired), is responsible for most relapses of cancer, one of the major causes of death of the disease. Heterogeneity among patients and tumors, and the versatility of cancer to circumvent therapies make drug resistance more challenging to deal with. Better understanding the mechanisms of drug resistance is required to provide guidance to future cancer treatment and achieve better outcomes. In this review, intrinsic and acquired resistance will be discussed. In addition, new discoveries in mechanisms of drug resistance will be reviewed. Particularly, we will highlight roles of ATP in drug resistance by discussing recent findings of exceptionally high levels of intratumoral extracellular ATP as well as intracellular ATP internalized from extracellular environment. The complexity of drug resistance development suggests that combinational and personalized therapies, which should take ATP into consideration, might provide better strategies and improved efficacy for fighting drug resistance in cancer.

Multiscale modeling reveals angiogenesis-induced drug resistance in brain tumors and predicts a synergistic drug combination targeting EGFR and VEGFR pathways

BACKGROUND

Experimental studies have demonstrated that both the extracellular vasculature or microenvironment and intracellular molecular network (e.g., epidermal growth factor receptor (EGFR) signaling pathway) are important for brain tumor growth. Additionally, some drugs have been developed to inhibit EGFR signaling pathways. However, how angiogenesis affects the response of tumor cells to drug treatment has rarely been mechanistically studied. Therefore, a multiscale model is required to investigate such complex biological systems that contain interactions and feedback among multiple levels.

RESULTS

In this study, we developed a single cell-based multiscale spatiotemporal model to simulate vascular tumor growth and the drug response based on the vascular endothelial growth factor receptor (VEGFR) signaling pathway, the EGFR signaling pathway and the cell cycle as well as several microenvironmental factors that determine cell fate switches in a temporal and spatial context. By incorporating the EGFRI treatment effect, the model showed an interesting phenomenon in which the survival rate of tumor cells decreased in the early stage but rebounded in a later stage, revealing the emergence of drug resistance. Moreover, we revealed the critical role of angiogenesis in acquired drug resistance, since inhibiting blood vessel growth using a VEGFR inhibitor prevented the recovery of the survival rate of tumor cells in the later stage. We further investigated the optimal timing of combining VEGFR inhibition with EGFR inhibition and predicted that the drug combination targeting both the EGFR pathway and VEGFR pathway has a synergistic effect. The experimental data validated the prediction of drug synergy, confirming the effectiveness of our model. In addition, the combination of EGFR and VEGFR genes showed clinical relevance in glioma patients.

CONCLUSIONS

The developed multiscale model revealed angiogenesis-induced drug resistance mechanisms of brain tumors to EGFRI treatment and predicted a synergistic drug combination targeting both EGFR and VEGFR pathways with optimal combination timing. This study explored the mechanistic and functional mechanisms of the angiogenesis underlying tumor growth and drug resistance, which advances our understanding of novel mechanisms of drug resistance and provides implications for designing more effective cancer therapies.

Long-term fluorescence hyperspectral imaging of on-chip treated co-culture tumour spheroids to follow clonal evolution

Multicellular tumour spheroids are an ideal in vitro tumour model to study clonal heterogeneity and drug resistance in cancer research because different cell types can be mixed at will. However, measuring the individual response of each cell population over time is challenging: current methods are either destructive, such as flow cytometry, or cannot image throughout a spheroid, such as confocal microscopy. Our group previously developed a wide-field fluorescence hyperspectral imaging system to study spheroids formed and cultured in microfluidic chips. In the present study, two subclones of a single parental ovarian cancer cell line transfected to express different fluorophores were produced and co-culture spheroids were formed on-chip using ratios forming highly asymmetric subpopulations. We performed a 3D proliferation assay on each cell population forming the spheroids that matched the 2D growth behaviour. Response assays to PARP inhibitors and platinum-based drugs were also performed to follow the clonal evolution of mixed populations. Our experiments show that hyperspectral imaging can detect spheroid response before observing a decrease in spheroid diameter. Hyperspectral imaging and microfluidic-based spheroid assays provide a versatile solution to study clonal heterogeneity, able to measure response in subpopulations presenting as little as 10% of the initial spheroid.

Cytoskeletal alteration modulates cancer cell invasion through RhoA-YAP signaling in stromal fibroblasts

Cancer-associated fibroblasts(CAFs) participate in carcinogenesis through interaction with cancer cells. This study aimed to investigate the mechanism of cytoskeletal alteration of CAFs and its role in invasion of oral squamous cell carcinoma(OSCC).Immortalized normal fibroblasts(hTERT-hNOFs) co-cultured with OSCC cells showed myofibroblastic and senescent phenotypes like CAFs. Thus, this study substituted hTERT-hNOFs for CAFs. Next, the cytoskeletal alteration and its molecular mechanism were investigated in hTERT-hNOFs co-cultured with OSCC. As results, we found that RhoA regulated cytoskeletal organization in fibroblasts surrounding OSCC cells. Furthermore, as a downstream transcriptional factor of RhoA, YAP was mainly localized in the nucleus of hTERT-hNOFs co-cultured with OSCC. Consequently, we examined whether nuclear YAP localization of fibroblasts could influence cancer progression. YAPS127A fibroblasts manifesting nuclear localization of YAP induced cytoskeletal alteration and increased gel contractility and matrix stiffness, and thereby enhances the invasiveness of OSCC cells. In conclusion, the modification of tumor microenvironment, such as cytoskeletal change and matrix remodeling via RhoA-YAP in CAFs, modulates OSCC invasion. These understandings will provide the development of novel approaches for CAFs-based cancer therapy.

Three-Dimensional Organoids in Cancer Research: The Search for the Holy Grail of Preclinical Cancer Modeling

Most solid tumors become therapy resistant and will relapse, with no durable treatment option available. One major impediment to our understanding of cancer biology and finding innovative approaches to cancer treatment stems from the lack of better preclinical tumor models that address and explain tumor heterogeneity and person-to-person differences in therapeutic and toxic responses. Past cancer research has been driven by inadequate in vitro assays utilizing two-dimensional monolayers of cancer cells and animal models. Additionally, animal models do not truly mimic the original human tumor, are time consuming, and usually costly. New preclinical models are needed for innovation in cancer translational research. Hence, it is time to welcome the three-dimensional (3D) organoids: self-organizing cells grown in 3D culture systems mimicking the parent tissues from which the primary cells originate. The 3D organoids offer deeper insights into the crucial cellular processes in tissue and organ formation and pathological processes. Generation of near-perfect physiological microenvironments allow 3D organoids to couple with gene editing tools, such as the clustered regularly interspersed short palindromic repeat (CRISPR)/CRISPR-associated 9 and the transcription activator-like effector nucleases to model human diseases, offering distinct advantages over current models. We explain in this expert review that through recapitulating patients' normal and tumor tissues, organoid technology can markedly advance personalized medicine and help reveal once hidden aspects of cancers. The use of defined tissue- or organ-specific matrices, among other factors, will likely allow organoid technology to realize its potential in innovating many fields of life sciences.

Polytherapy and Targeted Cancer Drug Resistance

A current challenge in cancer treatment is drug resistance. Even the most effective therapies often fail to produce a complete and durable tumor response and ultimately give rise to therapy resistance and tumor relapse. However, how resistance arises in cancer remains incompletely understood. While drug resistance in cancer is thought to be driven by irreversible genetic mutations, emerging evidence also implicates reversible proteomic and epigenetic mechanisms in the development of drug resistance. Tumor microenvironment-mediated mechanisms and tumor heterogeneity can significantly contribute to cancer treatment resistance. Here, we discuss the diverse and dynamic strategies that cancers use to evade drug response, the promise of upfront combination and intermittent therapies and therapy switching in forestalling resistance, and epigenetic reprogramming to combat resistance.

Epigenetic Modifications in Acute Myeloid Leukemia: Prognosis, Treatment, and Heterogeneity

Leukemia, specifically acute myeloid leukemia (AML), is a common malignancy that can be differentiated into multiple subtypes based on leukemogenic history and etiology. Although genetic aberrations, particularly cytogenetic abnormalities and mutations in known oncogenes, play an integral role in AML development, epigenetic processes have been shown as a significant and sometimes independent dynamic in AML pathophysiology. Here, we summarize how tumors evolve and describe AML through an epigenetic lens, including discussions on recent discoveries that include prognostics from epialleles, changes in RNA function for hematopoietic stem cells and the epitranscriptome, and novel epigenetic treatment options. We further describe the limitations of treatment in the context of the high degree of heterogeneity that characterizes acute myeloid leukemia.