Cancer heterogeneity: converting a limitation into a source of biologic information

Non-coding RNAs: a promising target for early metastasis intervention

ABSTRACT

Metastases account for the overwhelming majority of cancer-associated deaths. The dissemination of cancer cells from the primary tumor to distant organs involves a complex process known as the invasion-metastasis cascade. The underlying biological mechanisms of metastasis, however, remain largely elusive. Recently, the discovery and characterization of non-coding RNAs (ncRNAs) have revealed the diversity of their regulatory roles, especially as key contributors throughout the metastatic cascade. Here, we review recent progress in how three major types of ncRNAs (microRNAs, long non-coding RNAs, and circular RNAs) are involved in the multistep procedure of metastasis. We further examine interactions among the three ncRNAs as well as current progress in their regulatory mechanisms. We also propose the prevention of metastasis in the early stages of cancer progression and discuss current translational studies using ncRNAs as targets for metastasis diagnosis and treatments. These studies provide insights into developing more effective strategies to target metastatic relapse.

Automated multimodal fluorescence microscopy for hyperplex spatial-proteomics: Coupling microfluidic-based immunofluorescence to high resolution, high sensitivity, three-dimensional analysis of histological slides

In situ multiplexing analysis and in situ transcriptomics are now providing revolutionary tools to achieve the comprehension of the molecular basis of cancer and to progress towards personalized medicine to fight the disease. The complexity of these tasks requires a continuous interplay among different technologies during all the phases of the experimental procedures. New tools are thus needed and their characterization in terms of performances and limits is mandatory to reach the best resolution and sensitivity. We propose here a new experimental pipeline to obtain an optimized costs-to-benefits ratio thanks to the alternate employment of automated and manual procedures during all the phases of a multiplexing experiment from sample preparation to image collection and analysis. A comparison between ultra-fast and automated immunofluorescence staining and standard staining protocols has been carried out to compare the performances in terms of antigen saturation, background, signal-to-noise ratio and total duration. We then developed specific computational tools to collect data by automated analysis-driven fluorescence microscopy. Computer assisted selection of targeted areas with variable magnification and resolution allows employing confocal microscopy for a 3D high resolution analysis. Spatial resolution and sensitivity were thus maximized in a framework where the amount of stored data and the total requested time for the procedure were optimized and reduced with respect to a standard experimental approach.

The spatio-temporal evolution of multiple myeloma from baseline to relapse-refractory states

Deciphering Multiple Myeloma evolution in the whole bone marrow is key to inform curative strategies. Here, we perform spatial-longitudinal whole-exome sequencing, including 140 samples collected from 24 Multiple Myeloma patients during up to 14 years. Applying imaging-guided sampling we observe three evolutionary patterns, including relapse driven by a single-cell expansion, competing/co-existing sub-clones, and unique sub-clones at distinct locations. While we do not find the unique relapse sub-clone in the baseline focal lesion(s), we show a close phylogenetic relationship between baseline focal lesions and relapse disease, highlighting focal lesions as hotspots of tumor evolution. In patients with ≥3 focal lesions on positron-emission-tomography at diagnosis, relapse is driven by multiple distinct sub-clones, whereas in other patients, a single-cell expansion is typically seen (p < 0.01). Notably, we observe resistant sub-clones that can be hidden over years, suggesting that a prerequisite for curative therapies would be to overcome not only tumor heterogeneity but also dormancy.

Angiotensin-converting Enzyme Insertion/Deletion Polymorphism (rs4646994) and Susceptibility to Acute Lymphoblastic Leukemia: A Case–control Study

BACKGROUND: Angiotensin-converting enzyme (ACE) stimulates the proliferation of bone marrow hematopoietic progenitors and thought to be involved in pathological neoplastic hematopoiesis and leukemogenesis. AIM: This study aimed to investigate the association between ACE gene I/D polymorphism and the risk of acute lymphoblastic leukemia (ALL). MATERIALS AND METHODS: A total of 96 subjects were recruited for the study, 48 patients with ALL, and 48 apparently healthy volunteers as a control group. Genomic DNA was extracted from peripheral leukocytes and ACE I/D polymorphism was analysed using allele-specific polymerase chain reaction. RESULTS: In both study groups, the ACE D/D polymorphic genotype was the most frequent (52.1% and 54.2%, respectively), followed by the ID genotype (47.9% and 45.8% respectively), while the II genotype was completely absent in both study groups. The distribution of the polymorphic genotypes among the study groups was not significantly different (p = 0. 0.398). The frequency of the D allele was 0.76 in the patients and 0.77 in the control group, while the frequency of I allele was 0.24 in the patients and 0.23 in the control group. No deviation from Hardy–Weinberg equilibrium was observed (χ2 = 4.24, df = 1, p = 0.12). CONCLUSION: ACE I/D polymorphism is not associated with susceptibility to ALL among the Sudanese population.

Liquid biopsy = Individualized cancer management: Diagnosis, monitoring treatment and checking recurrence and metastasis

Traditional cancer-screening techniques such as imaging and protein biomarkers are not sufficient for early detection. Various forms of endoscopy and tumour biopsy are the current standard methods in diagnosing Head Neck Cancers. Liquid biopsy has been increasingly considered as an option for molecular characterization and detection of cancer as it can provide real-time information about cancer in a minimally invasive manner. Circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), and exosomal miRNAs are emerging biomarkers that can be applied to cancer detection, treatment planning, and response monitoring. A 'liquid biopsy' presents an option where the disease can be tracked in a less-invasive, simple manner, allowing for serial sampling informing of the tumour heterogeneity, response to treatment and minimal residual disease.

Swiss-PO: a new tool to analyze the impact of mutations on protein three-dimensional structures for precision oncology

Swiss-PO is a new web tool to map gene mutations on the 3D structure of corresponding proteins and to intuitively assess the structural implications of protein variants for precision oncology. Swiss-PO is constructed around a manually curated database of 3D structures, variant annotations, and sequence alignments, for a list of 50 genes taken from the Ion AmpliSeqTM Custom Cancer Hotspot Panel. The website was designed to guide users in the choice of the most appropriate structure to analyze regarding the mutated residue, the role of the protein domain it belongs to, or the drug that could be selected to treat the patient. The importance of the mutated residue for the structure and activity of the protein can be assessed based on the molecular interactions exchanged with neighbor residues in 3D within the same protein or between different biomacromolecules, its conservation in orthologs, or the known effect of reported mutations in its 3D or sequence-based vicinity. Swiss-PO is available free of charge or login at https://www.swiss-po.ch .

Cancer evolution: A means by which tumors evade treatment

Although various methods have been tried to study and treat cancer, the cancer remains a major challenge for human medicine today. One important reason for this is the presence of cancer evolution. Cancer evolution is a process in which tumor cells adapt to the external environment, which can suppress the human immune system's ability to recognize and attack tumors, and also reduce the reproducibility of cancer research. Among them, heterogeneity of the tumor provides intrinsic motivation for this process. Recently, with the development of related technologies such as liquid biopsy, more and more knowledge about cancer evolution has been gained and interest in this topic has also increased. Therefore, starting from the causes of tumorigenesis, this paper introduces several tumorigenesis processes and pathways, as well as treatment options for different targets.

Intratumor Heterogeneity of MYO18A and FBXW7 Variants Impact the Clinical Outcome of Stage III Colorectal Cancer

Many studies failed to demonstrate benefit from the addition of targeted agents to current standard adjuvant FOLFOX chemotherapy in stage III colorectal cancer (CRC) patients. Intratumor heterogeneity may foster the resistant subclones and leads to cancer recurrence. Here, we built a cancer evolution model and applied machine learning analysis to identify potential therapeutic targets. Among 78 CRC cases, whole-genome (WGS) and deep targeted sequencing data generated from paired blood and primary tumor were used for phylogenetic tree reconstruction. Genetic alterations in the PI3K/AKT, and RTK oncogenic signaling pathways were commonly detected in founding clones. The dominant subclones frequently exhibited dysregulations in the TP53, FBXW7/NOTCH1 tumor suppression, and DNA repair pathways. Fourteen genetic mutations were simultaneously selected by random forest and LASSO methods. The logistic regression model had better accuracy (79%), precision (70%), and recall (65%) and area under the curve (AUC) (82%) for cancer recurrence prediction. Three genes, including MYO18A in the founding clone, FBXW7, and ATM in the dominant subclone, affected the prognosis were selected simultaneously by different feature sets. The in vitro studies, HCT-116 cells transfected with MYO18A siRNA demonstrated a significant reduction in cell migration activity by 20-40%. These results indicate that MYO18A plays a crucial role in the migration of human CRC cells. The cancer evolution model revealed the critical mutations in the founding and dominant subclones. They can be used to predict clinical outcomes and the development of novel therapeutic targets for stage III CRC.

An engineered pancreatic cancer model with intra-tumoral heterogeneity of driver mutations

Pancreatic ductal adenocarcinoma (PDAC) is a complex disease with significant intra-tumoral heterogeneity (ITH). Currently, no reliable PDAC tumor model is available that can present ITH profiles in a controlled manner. We develop an in vitro microfluidic tumor model mimicking the heterogeneous accumulation of key driver mutations of human PDAC using cancer cells derived from genetically engineered mouse models. These murine pancreatic cancer cell lines have KPC (Kras and Trp53 mutations) and KIC genotypes (Kras mutation and Cdkn2a deletion). Also, the KIC genotypes have two distinct phenotypes - mesenchymal or epithelial. The tumor model mimics the ITH of human PDAC to study the effects of ITH on the gemcitabine response. The results show gemcitabine resistance induced by ITH. Remarkably, it shows that cancer cell-cell interactions induce the gemcitabine resistance potentially through epithelial-mesenchymal-transition. The tumor model can provide a useful testbed to study interaction mechanisms between heterogeneous cancer cell subpopulations.

From the Broad Phase II Trial to Precision Oncology: A Perspective on the Origins of Basket and Umbrella Clinical Trial Designs in Cancer Drug Development

Oncologic phase II trials that evaluate the activity of new therapeutic agents have evolved dramatically over the past 50 years. The standard approach beginning in the late 1960s focused on individual studies that evaluated new anticancer agents against a wide range of both solid and hematopoietic malignancies often in a single "broad phase II trial" that included hundreds of patients; such studies efficiently established the landscape for subsequent development of a specific drug with respect to likely disease focus, toxicity, dose, and schedule. In the 1980s and 1990s, emphasis on histological context drove an explosion in the number of individual phase II trials conducted; despite this increase in trial activity, investigations based on histology per se failed to improve the success rate of new agents brought to the clinic. Over the past 20 years, evolution toward a molecular drug development paradigm has demonstrably improved our ability to select patients more likely to benefit from systemic treatment; simultaneously, technological advances have permitted initial attempts at the rapid assignment of therapy based on predefined molecular characteristics of tumor or germline in broad-based master protocols that are inclusive of many diseases and molecularly characterized disease subsets, akin to but much more sophisticated scientifically than the broad phase II platforms of the past.

DECO: decompose heterogeneous population cohorts for patient stratification and discovery of sample biomarkers using omic data profiling

Motivation

Patient and sample diversity is one of the main challenges when dealing with clinical cohorts in biomedical genomics studies. During last decade, several methods have been developed to identify biomarkers assigned to specific individuals or subtypes of samples. However, current methods still fail to discover markers in complex scenarios where heterogeneity or hidden phenotypical factors are present. Here, we propose a method to analyze and understand heterogeneous data avoiding classical normalization approaches of reducing or removing variation.

Results

DEcomposing heterogeneous Cohorts using Omic data profiling (DECO) is a method to find significant association among biological features (biomarkers) and samples (individuals) analyzing large-scale omic data. The method identifies and categorizes biomarkers of specific phenotypic conditions based on a recurrent differential analysis integrated with a non-symmetrical correspondence analysis. DECO integrates both omic data dispersion and predictor–response relationship from non-symmetrical correspondence analysis in a unique statistic (called h-statistic), allowing the identification of closely related sample categories within complex cohorts. The performance is demonstrated using simulated data and five experimental transcriptomic datasets, and comparing to seven other methods. We show DECO greatly enhances the discovery and subtle identification of biomarkers, making it especially suited for deep and accurate patient stratification.

Availability and implementation

DECO is freely available as an R package (including a practical vignette) at Bioconductor repository (http://bioconductor.org/packages/deco/).

Supplementary information

Supplementary data are available at Bioinformatics online.

Efficacy of direct current generated by multiple-electrode arrays on F3II mammary carcinoma: experiment and mathematical modeling

Background

The modified Gompertz equation has been proposed to fit experimental data for direct current treated tumors when multiple-straight needle electrodes are individually inserted into the base perpendicular to the tumor long axis. The aim of this work is to evaluate the efficacy of direct current generated by multiple-electrode arrays on F3II mammary carcinoma that grow in the male and female BALB/c/Cenp mice, when multiple-straight needle electrodes and multiple-pairs of electrodes are inserted in the tumor.

Methods

A longitudinal and retrospective preclinical study was carried out. Male and female BALB/c/Cenp mice, the modified Gompertz equation, intensities (2, 6 and 10 mA) and exposure times (10 and 20 min) of direct current, and three geometries of multiple-electrodes (one formed by collinear electrodes and two by pair-electrodes) were used. Tumor volume and mice weight were measured. In addition, the mean tumor doubling time, tumor regression percentage, tumor growth delay, direct current overall effectiveness and mice survival were calculated.

Results

The greatest growth retardation, mean doubling time, regression percentage and growth delay of the primary F3II mammary carcinoma in male and female mice were observed when the geometry of multiple-pairs of electrodes was arranged in the tumor at 45, 135, 225 and 325^o and the longest exposure time. In addition, highest direct current overall effectiveness (above 66%) was observed for this EChT scheme.

Conclusions

It is concluded that electrochemical therapy may be potentially addressed to highly aggressive and metastic primary F3II murine mammary carcinoma and the modified Gompertz equation may be used to fit data of this direct current treated carcinoma. Additionally, electrochemical therapy effectiveness depends on the exposure time, geometry of multiple-electrodes and ratio between the direct current intensity applied and the polarization current induced in the tumor.

Genomics and the History of Precision Oncology

Progress toward the implementation of a molecular characterization paradigm in cancer drug development over the past 20 years has markedly enhanced our capability to select patients who are more likely to benefit from cancer therapy. Improvements in genomic and related diagnostic testing platforms have permitted evaluation of the efficacy of treatment assignment based on predefined biologic features of a patient's tumor or germline using master protocols that may include many malignancies and their molecularly characterized subsets. With this approach, a wide range of new targeted and immunologic treatment approaches have been defined for patients who, heretofore, lacked effective therapeutic options.

Pyruvate Kinase M2: a Metabolic Bug in Re-Wiring the Tumor Microenvironment

Metabolic reprogramming is a newly emerged hallmark of cancer attaining a recent consideration as an essential factor for the progression and endurance of cancer cells. A prime event of this altered metabolism is increased glucose uptake and discharge of lactate into the cells surrounding constructing a favorable tumor niche. Several oncogenic factors help in promoting this consequence including, pyruvate kinase M2 (PKM2) a rate-limiting enzyme of glycolysis in tumor metabolism via exhibiting its low pyruvate kinase activity and nuclear moon-lightening functions to increase the synthesis of lactate and macromolecules for tumor proliferation. Not only its role in cancer cells but also its role in the tumor microenvironment cells has to be understood for developing the small molecules against it which is lacking with the literature till date. Therefore, in this present review, the role of PKM2 with respect to various tumor niche cells will be clarified. Further, it highlights the updated list of therapeutics targeting PKM2 pre-clinically and clinically with their added limitations. This upgraded understanding of PKM2 may provide a pace for the reader in developing chemotherapeutic strategies for better clinical survival with limited resistance.

Effects of mutations and immunogenicity on outcomes of anti-cancer therapies for secondary lesions

Cancer development is driven by mutations and selective forces, including the action of the immune system and interspecific competition. When administered to patients, anti-cancer therapies affect the development and dynamics of tumours, possibly with various degrees of resistance due to immunoediting and microenvironment. Tumours are able to express a variety of competing phenotypes with different attributes and thus respond differently to various anti-cancer therapies. In this paper, a mathematical framework incorporating a system of delay differential equations for the immune system activation cycle and an agent-based approach for tumour-immune interaction is presented. The focus is on those metastatic, secondary solid lesions that are still undetected and non-vascularised. By using available experimental data, we analyse the effects of combination therapies on these lesions and investigate the role of mutations on the rates of success of common treatments. Findings show that mutations, growth properties and immunoediting influence therapies' outcomes in nonlinear and complex ways, affecting cancer lesion morphologies, phenotypical compositions and overall proliferation patterns. Cascade effects on final outcomes for secondary lesions are also investigated, showing that actions on primary lesions could sometimes result in unexpected clearances of secondary tumours. This outcome is strongly dependent on the clonal composition of the primary and secondary masses and is shown to allow, in some cases, the control of the disease for years.

Single‑cell intratumoral stemness analysis reveals the involvement of cell cycle and DNA damage repair in two different types of esophageal cancer

Intratumoral heterogeneity, particularly the potential cancer stemness of single cancer cells, has not yet been fully elucidated in human esophageal cancer. Single‑cell transcriptome sequencing of two types of esophageal adenocarcinoma (EAC) and two types of esophageal squamous cell carcinoma (ESCC) tissues was performed, and the intratumoral cancer stemness of the types of esophageal cancer were characterized at the single‑cell level in the present study. By comparing the transcriptomic profiles of single cancer cells with high and low stemness in individual patients, it was revealed that the overexpression of cell cycle‑associated genes in EAC cells was highly correlated with stemness, whereas overexpression of genes involved in the signaling pathways of DNA replication and DNA damage repair was significantly correlated with stemness in ESCC. High expression of these stemness‑associated genes was correlated with poor prognosis of patients. Additionally, poly [ADP‑ribose] polymerase(PARP)4 was identified as a novel cancer stemness‑associated gene in ESCC and its association with survival was validated in a cohort of 121 patients with ESCC. These findings have profound potential implications for the use of cell cycle inhibitors in EAC and PARP inhibitors in ESCC, which may provide novel mechanistic insights into the plasticity of esophageal cancer.

Liquid Biopsy in Oral Cancer

Oral cancer is one of the most prevalent forms of cancer worldwide. Carcinogenesis is a complex process, in which heterogeneity plays an important role in the development and progression of the disease. This review provides an overview of the current biological and clinical significance of circulating tumour cells (CTCs), circulating tumour DNA (ctDNA), and exosomes for diagnosis and prognosis of oral cancer. We highlight the importance of liquid biopsy—using blood and saliva—which represents a potential alternative to solid biopsy for diagnosis and prognosis. Moreover, liquid biomarkers allow for the real-time monitoring of tumour evolution and therapeutic responses, initiating the era of personalized medicine. However, in oral cancer, the impact of liquid biopsies in clinical settings is still limited, requiring further studies to discover the best scenario for its clinical use.