Quantitative evidence for early metastatic seeding in colorectal cancer

Mechanisms of small cell lung cancer metastasis

Metastasis is a major cause of morbidity and mortality in cancer patients. However, the molecular and cellular mechanisms underlying the ability of cancer cells to metastasize remain relatively poorly understood. Among all solid tumors, small cell lung cancer (SCLC) has remarkable metastatic proclivity, with a majority of patients diagnosed with metastatic disease. Our understanding of SCLC metastasis has been hampered for many years by the paucity of material from primary tumors and metastases, as well as the lack of faithful pre-clinical models. Here, we review recent advances that are helping circumvent these limitations. These advances include methods that employ circulating tumor cells from the blood of SCLC patients and the development of diverse genetically engineered mouse models of metastatic SCLC. New insights into the cellular mechanisms of SCLC metastasis include observations of cell fate changes associated with increased metastatic ability. Ongoing studies on cell migration and organ tropism promise to expand our understanding of SCLC metastasis. Ultimately, a better molecular understanding of metastatic phenotypes may be translated into new therapeutic options to limit metastatic spread and treat metastatic SCLC.

Genomic and prognostic heterogeneity among RAS/BRAFV600E /TP53 co-mutated resectable colorectal liver metastases

Hepatic resection is potentially curative for patients with colorectal liver metastases, but the treatment benefit varies. KRAS/NRAS (RAS)/TP53 co‐mutations are associated with a poor prognosis after resection, but there is large variation in patient outcome within the mutation groups, and genetic testing is currently not used to evaluate benefit from surgery. We have investigated the potential for improved prognostic stratification by combined biomarker analysis with DNA copy number aberrations (CNAs), and taking tumor heterogeneity into account. We determined the mutation status of RAS, BRAF^V600, and TP53 in 441 liver lesions from 171 patients treated by partial hepatectomy for metastatic colorectal cancer. CNAs were profiled in 232 tumors from 67 of the patients. Mutations and high‐level amplifications of cancer‐critical genes, the latter including ERBB2 and EGFR, were predominantly homogeneous within patients. RAS/BRAF^V600E and TP53 co‐mutations were associated with a poor patient outcome (hazard ratio, HR, 3.9, 95% confidence interval, CI, 1.3–11.1, P = 0.012) in multivariable analyses with clinicopathological variables. The genome‐wide CNA burden and intrapatient intermetastatic CNA heterogeneity varied within the mutation groups, and the CNA burden had prognostic associations in univariable analysis. Combined prognostic analyses of RAS/BRAF^V600E/TP53 mutations and CNAs, either as a high CNA burden or high intermetastatic CNA heterogeneity, identified patients with a particularly poor outcome (co‐mutation/high CNA burden: HR 2.7, 95% CI 1.2–5.9, P = 0.013; co‐mutation/high CNA heterogeneity: HR 2.5, 95% CI 1.1–5.6, P = 0.022). In conclusion, DNA copy number profiling identified genomic and prognostic heterogeneity among patients with resectable colorectal liver metastases with co‐mutated RAS/BRAF^V600E/TP53.

Role of myeloid-derived suppressor cells in metastasis

The spread of primary tumor cells to distant organs, termed metastasis, is the principal cause of cancer mortality and is a critical therapeutic target in oncology. Thus, a better understanding of metastatic progression is critical for improved therapeutic approaches requiring insight into the timing of tumor cell dissemination and seeding of distant organs, which can lead to the formation of occult lesions. However, due to limitations in imaging techniques, primary tumors can only be detected when they reach a relatively large size (e.g., > 1 cm³), which, based on our understanding of tumor evolution, is 10 to 20 years (30 doubling times) following tumor initiation. Recent insights into the timing of metastasis are based on the genomic profiling of paired primary tumors and metastases, suggesting that tumor cell seeding of secondary sites occurs early during tumor progression and years prior to diagnosis. Following seeding, tumor cells may remain in a dormant state as single cells or micrometastases before emerging as overt lesions. This timeline and the role of metastatic dormancy are regulated by interactions between the tumor, its microenvironment, and tumor-specific T cell responses. An improved understanding of the mechanisms and interactions responsible for immune evasion and tumor cell release from dormancy would support the development of novel targeted therapeutics. We posit herein that the immunosuppressive mechanisms mediated by myeloid-derived suppressor cells (MDSCs) are a major contributor to tumor progression, and that these mechanisms promote tumor cell escape from dormancy. Thus, while extensive studies have demonstrated a role for MDSCs in the escape from adoptive and innate immune responses (T-, natural killer (NK)-, and B cell responses), facilitating tumor progression and metastasis, few studies have considered their role in dormancy. In this review, we discuss the role of MDSC expansion, driven by tumor burden, and its role in escape from dormancy, resulting in occult metastases, and the potential for MDSC inhibition as an approach to prolong the survival of patients with advanced malignancies.

Metastasis Initiation Precedes Detection of Primary Cancer-Analysis of Metastasis Growth in vivo in a Colorectal Cancer Test Case

Most cases of deaths from colorectal cancer (CRC) result from metastases, which are often still undetectable at disease detection time. Even so, in many cases, shedding is assumed to have taken place before that time. The dynamics of metastasis formation and growth are not well-established. This work aims to explore CRC lung metastasis growth rate and dynamics. We analyzed a test case of a metastatic CRC patient with four lung metastases, with data of four serial computed tomography (CT) scans measuring metastasis sizes while untreated. We fitted three mathematical growth models—exponential, logistic, and Gompertzian—to the CT measurements. For each metastasis, a best-fitted model was determined, tumor doubling time (TDT) was assessed, and metastasis inception time was extrapolated. Three of the metastases showed exponential growth, while the fourth showed logistic restraint of the growth. TDT was around 93 days. Predicted metastasis inception time was at least 4–5 years before the primary tumor diagnosis date, though they did not reach detectable sizes until at least 1 year after primary tumor resection. Our results support the exponential growth approximation for most of the metastases, at least for the clinically observed time period. Our analysis shows that metastases can be initiated before the primary tumor is detectable and implies that surgeries accelerate metastasis growth.

Genomic control of metastasis

Metastasis remains the leading cause of cancer-associated mortality, and a detailed understanding of the metastatic process could suggest new therapeutic avenues. However, how metastatic phenotypes arise at the genomic level has remained a major open question in cancer biology. Comparative genetic studies of primary and metastatic cancers have revealed a complex picture of metastatic evolution with diverse temporal patterns and trajectories to dissemination. Whole-genome amplification is associated with metastatic cancer clones, but no metastasis-exclusive driver mutations have emerged. Instead, genetically activated oncogenic pathways that drive tumour initiation and early progression acquire metastatic traits by co-opting physiological programmes from stem cell, developmental and regenerative pathways. The functional consequences of oncogenic driver mutations therefore change via epigenetic mechanisms to promote metastasis. Increasing evidence is starting to uncover the molecular mechanisms that determine how specific oncogenic drivers interact with various physiological programmes, and what triggers their activation in support of metastasis. Detailed insight into the mechanisms that control metastasis is likely to reveal novel opportunities for intervention at different stages of metastatic progression.

Neuroendocrine Tumor Omic Gene Cluster Analysis Amplifies the Prognostic Accuracy of the NETest

BACKGROUND

The NETest is a multigene assay comprising 51 circulating neuroendocrine tumor (NET)-specific transcripts. The quotient of the 51-gene assay is based upon an ensemble of machine learning algorithms. Eight cancer hallmarks or "omes" (apoptome, epigenome, growth factor signalome, metabolome, proliferome, plurome, secretome, SSTRome) represent 29 genes. The NETest is an accurate diagnostic (>90%) test, but its prognostic utility has not been assessed. In this study, we describe the expansion of the NETest omic cluster components and demonstrate that integration amplifies NETest prognostic accuracy.

METHODS

Group 1: n = 222; including stable disease (SD, n = 146), progressive disease (PD, n = 76), and controls (n = 139). Group 2: NET Registry NCT02270567; n = 88; prospective samples (SD, n = 54; PD, n = 34) with up to 24 months follow-up. We used PubMed literature review, interactomic analysis, nonparametric testing, Kaplan-Meier survival curves, and χ2 analyses to inform and define the prognostic significance of NET genomic "hallmarks."

RESULTS

2020 analyses: In-depth analyses of 47 -NETest genes identified a further six omes: fibrosome, inflammasome, metastasome, NEDome, neurome, and TFome. Group 1 analysis: Twelve omes, excluding the inflammasome and apoptome, were significantly (p < 0.05, 2.1- to 8.2-fold) elevated compared to controls. In the PD group, seven omes (proliferome, NEDome, epigenome, SSTRome, neurome, metastasome, and fibrosome) were elevated (both expression levels and fold change >2) versus SD. Group 2 analysis: All these seven omes were upregulated. In PD, they were significantly more elevated (p < 0.02) than in SD. The septet omic expression exhibited a 69% prognostic accuracy. The NETest alone was 70.5% accurate. A low NETest (≤40) integrated with epigenome/metastasome levels was an accurate prognostic for PD (90%). A high NETest (>40) including the fibrosome/NEDome predicted PD development within 3 months (100%). Using decision tree analysis to integrate the four omes (epigenome, metastasome, fibrosome, and NEDome) with the NETest score generated an overall prognostic accuracy of 93%.

CONCLUSIONS

Examination of NETest omic gene cluster analysis identified five additional clinically relevant cancer hallmarks. Identification of seven omic clusters (septet) provides a molecular pathological signature of disease progression. The integration of the quartet (epigenome, fibrosome, metastasome, NEDome) and the NETest score yielded a 93% accuracy in the prediction of future disease status.

Potential alteration of tumor microenvironments by β-mercaptoethanol

The therapeutic effectiveness of immune checkpoint inhibitors in cancer patients is quite profound. However, it is generally accepted that further progress is curtailed by accompanying adverse events and by low cure rates linked to the tumor microenvironment. The multitudes of immune processes altered by low-molecular-weight thiols published over the past decades suggest they have potential to alter tumor microenvironment processes which could result in an increase in immune checkpoint inhibitor survival rates. Based on one of the most studied and most potent low-molecular-weight thiols, β-mercaptoethanol (BME), it is proposed that clinical assessment be undertaken to identify any BME benefits with relevance for proliferation/differentiation of immune cells, lymphocyte exhaustion, immunogenicity of tumor antigens and inactivation of suppressor cells/factors. The BME alterations projected to be most effective are: maintenance/replacement of glutathione in lymphocytes via facilitation of cysteine uptake, inhibition of suppressor cells/soluble factors and inactivation of free-radical, reactive oxygen species.

Optimal Timing for Cancer Screening and Adaptive Surveillance Using Mathematical Modeling

Cancer screening and early detection efforts have been partially successful in reducing incidence and mortality, but many improvements are needed. Although current medical practice is informed by epidemiologic studies and experts, the decisions for guidelines are ultimately ad hoc. We propose here that quantitative optimization of protocols can potentially increase screening success and reduce overdiagnosis. Mathematical modeling of the stochastic process of cancer evolution can be used to derive and optimize the timing of clinical screens so that the probability is maximal that a patient is screened within a certain "window of opportunity" for intervention when early cancer development may be observable. Alternative to a strictly empirical approach or microsimulations of a multitude of possible scenarios, biologically based mechanistic modeling can be used for predicting when best to screen and begin adaptive surveillance. We introduce a methodology for optimizing screening, assessing potential risks, and quantifying associated costs to healthcare using multiscale models. As a case study in Barrett's esophagus, these methods were applied for a model of esophageal adenocarcinoma that was previously calibrated to U.S. cancer registry data. Optimal screening ages for patients with symptomatic gastroesophageal reflux disease were older (58 for men and 64 for women) than what is currently recommended (age > 50 years). These ages are in a cost-effective range to start screening and were independently validated by data used in current guidelines. Collectively, our framework captures critical aspects of cancer evolution within patients with Barrett's esophagus for a more personalized screening design. SIGNIFICANCE: This study demonstrates how mathematical modeling of cancer evolution can be used to optimize screening regimes, with the added potential to improve surveillance regimes. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/81/4/1123/F1.large.jpg.

Performance-weighted-voting model: An ensemble machine learning method for cancer type classification using whole-exome sequencing mutation

Background

With improvements in next-generation DNA sequencing technology, lower cost is needed to collect genetic data. More machine learning techniques can be used to help with cancer analysis and diagnosis.

Methods

We developed an ensemble machine learning system named performance-weighted-voting model for cancer type classification in 6,249 samples across 14 cancer types. Our ensemble system consists of five weak classifiers (logistic regression, SVM, random forest, XGBoost and neural networks). We first used cross-validation to get the predicted results for the five classifiers. The weights of the five weak classifiers can be obtained based on their predictive performance by solving linear regression functions. The final predicted probability of the performance-weighted-voting model for a cancer type can be determined by the summation of each classifier's weight multiplied by its predicted probability.

Results

Using the somatic mutation count of each gene as the input feature, the overall accuracy of the performance-weighted-voting model reached 71.46%, which was significantly higher than the five weak classifiers and two other ensemble models: the hard-voting model and the soft-voting model. In addition, by analyzing the predictive pattern of the performance-weighted-voting model, we found that in most cancer types, higher tumor mutational burden can improve overall accuracy.

Conclusion

This study has important clinical significance for identifying the origin of cancer, especially for those where the primary cannot be determined. In addition, our model presents a good strategy for using ensemble systems for cancer type classification.

Metabolic regulation of prostate cancer heterogeneity and plasticity

Metabolic reprogramming is one of the main hallmarks of cancer cells. It refers to the metabolic adaptations of tumor cells in response to nutrient deficiency, microenvironmental insults, and anti-cancer therapies. Metabolic transformation during tumor development plays a critical role in the continued tumor growth and progression and is driven by a complex interplay between the tumor mutational landscape, epigenetic modifications, and microenvironmental influences. Understanding the tumor metabolic vulnerabilities might open novel diagnostic and therapeutic approaches with the potential to improve the efficacy of current tumor treatments. Prostate cancer is a highly heterogeneous disease harboring different mutations and tumor cell phenotypes. While the increase of intra-tumor genetic and epigenetic heterogeneity is associated with tumor progression, less is known about metabolic regulation of prostate cancer cell heterogeneity and plasticity. This review summarizes the central metabolic adaptations in prostate tumors, state-of-the-art technologies for metabolic analysis, and the perspectives for metabolic targeting and diagnostic implications.

Mutation-selection balance and compensatory mechanisms in tumour evolution

Intratumour heterogeneity and phenotypic plasticity, sustained by a range of somatic aberrations, as well as epigenetic and metabolic adaptations, are the principal mechanisms that enable cancers to resist treatment and survive under environmental stress. A comprehensive picture of the interplay between different somatic aberrations, from point mutations to whole-genome duplications, in tumour initiation and progression is lacking. We posit that different genomic aberrations generally exhibit a temporal order, shaped by a balance between the levels of mutations and selective pressures. Repeat instability emerges first, followed by larger aberrations, with compensatory effects leading to robust tumour fitness maintained throughout the tumour progression. A better understanding of the interplay between genetic aberrations, the microenvironment, and epigenetic and metabolic cellular states is essential for early detection and prevention of cancer as well as development of efficient therapeutic strategies.

Recent Advances on Rare Earth Upconversion Nanomaterials for Combined Tumor Near-Infrared Photoimmunotherapy

Cancer has been threatening the safety of human life. In order to treat cancer, many methods have been developed to treat tumor, such as traditional therapies like surgery, chemotherapy, radiotherapy, as well as new strategies like photodynamic therapy, photothermal therapy, sonodynamic therapy, and other emerging therapies. Although there are so many ways to treat tumors, these methods all face the dilemma that they are incapable to cope with metastasis and recurrence of tumors. The emergence of immunotherapy has given the hope to conquer the challenge. Immunotherapy is to use the body's own immune system to stimulate and maintain a systemic immune response to form immunological memory, resist the metastasis and recurrence of tumors. At the same time, immunotherapy can combine with other treatments to exhibit excellent antitumor effects. Upconversion nanoparticles (UCNPs) can convert near-infrared (NIR) light into ultraviolet and visible light, thus have good performance in bioimaging and NIR triggered phototherapy. In this review paper, we summarize the design, fabrication, and application of UCNPs-based NIR photoimmunotherapy for combined cancer treatment, as well as put forward the prospect of future development.

The expression of seven key genes can predict distant metastasis of colorectal cancer to the liver or lung

OBJECTIVE

It is unclear how primary colorectal cancer (CRC) cells select to metastasize to the liver or lungs, the most frequent distant metastasis of CRC. We aimed to identify the key genes and pathways that may predict the distant metastasis of CRC to these sites.

METHODS

Three gene expression array datasets from the Gene Expression Omnibus were analyzed. Protein-protein network analyses, best subsets regressions and backward stepwise regression analyses were used to screen the key genes and their expressions were used to construct a predictive logistic regression model. Expression data from local clinical samples were used as a validation dataset. The receiver operating characteristic (ROC) curve was used to test the performance of the predictive model.

RESULTS

In total, 59 differentially expressed genes (DEG) related to liver-metastasis, 90 related to lung metastasis and 45 related to both liver and lung metastasis were identified. The KEGG pathways and gene oncology (GO) terms that were enriched in liver and lung metastasis were identified. A predictive logistic regression model consisted of SPARC, COL1A2, MMP9, COL11A1, COL3A1, CXCL12 and THBS2 was established. The area under the ROC curve reached 0.839 in predicting liver and lung metastasis, using our clinical samples as the validation dataset.

CONCLUSIONS

Seven key genes capable of predicting liver and lung metastasis of colorectal cancer were identified, which provides clues for exploring the mechanism of selecting target organs during the metastatic process in CRC and inspires the researches for new potential targets for therapy to inhibit metastasis.

Cancer progression and the invisible phase of metastatic colonization

Metastatic dissemination occurs very early in the malignant progression of a cancer but the clinical manifestation of metastases often takes years. In recent decades, 5-year survival of patients with many solid cancers has increased due to earlier detection, local disease control and adjuvant therapies. As a consequence, we are confronted with an increase in late relapses as more antiproliferative cancer therapies prolong disease courses, raising questions about how cancer cells survive, evolve or stop growing and finally expand during periods of clinical latency. I argue here that the understanding of early metastasis formation, particularly of the currently invisible phase of metastatic colonization, will be essential for the next stage in adjuvant therapy development that reliably prevents metachronous metastasis.

Functional Pro-metastatic Heterogeneity Revealed by Spiked-scRNAseq Is Shaped by Cancer Cell Interactions and Restricted by VSIG1

How cells with metastatic potential, or pro-metastatic states, arise within heterogeneous primary tumors remains unclear. Here, we have used one index primary colon cancer to develop spiked-scRNAseq to link omics-defined single-cell clusters with cell behavior. Using spiked-scRNAseq we uncover cell populations with differential metastatic potential in which pro-metastatic states are correlated with the expression of signaling and vesicle-trafficking genes. Analyzing such heterogeneity, we define an anti-metastatic, non-cell-autonomous interaction originating from non-/low-metastatic cells, and identify membrane VSIG1 as a critical mediator of this interaction. VSIG1 acts to restrict the development of pro-metastatic states autonomously and non-cell autonomously, in part by inhibiting YAP/TAZ-TEAD signaling. As VSIG1 re-expression is able to reduce metastatic behavior from multiple colon cancer cell types, the regulation of VSIG1 or its effectors opens new interventional opportunities. In general, we propose that crosstalk between cancer cells, including the action of VSIG1, dynamically defines the degree of pro-metastatic intra-tumoral heterogeneity.

[Genetic instability, a factor limiting the efficiency of targeted therapies in solid oncology]

Genomic instability is one of the main properties of tumour development, promoting first the acquisition of genetic alterations and thus carcinogenesis. Then, the chronic and anarchic proliferation of cancer cells also supports and contributes to this instability allowing a continuous evolution of the tumour. The accumulation of mutations resulting from that instability contributes to tumour heterogeneity that occurs in a specific environment. The resulting diversity of oncogenic drivers further complicates the characterization of the origin of cancer cells dysfunction and consequently therapeutic decision. However, the consideration of the molecular context in oncology has initiated the development of targeted therapies. Based on the concept of oncogene addiction and synthetic lethality, these new drugs require the characterization and identification of specific tumour biomarkers. Targeted therapies have thus considerably optimized patient management, improving efficiency and quality of life while limiting the side effects observed with conventional chemotherapies. However, despite significant clinical benefits, some major limitations to their administration remain. The study of the current issues related to these new therapeutic molecules is becoming crucial for patient management towards an improvement of personalized medicine.

Genetic Alterations of Metastatic Colorectal Cancer

Genome sequencing studies have characterized the genetic alterations of different tumor types, highlighting the diversity of the molecular processes driving tumor development. Comprehensive sequencing studies have defined molecular subtypes of colorectal cancers (CRCs) through the identification of genetic events associated with microsatellite stability (MSS), microsatellite-instability-high (MSI-H), and hypermutation. Most of these studies characterized primary tumors. Only recent studies have addressed the characterization of the genetic and clinical heterogeneity of metastatic CRC. Metastatic CRC genomes were found to be not fundamentally different from primary CRCs in terms of the mutational landscape or of genes that drive tumorigenesis, and a genomic heterogeneity associated with tumor location of primary tumors helps to define different clinical behaviors of metastatic CRCs. Although CRC metastatic spreading was traditionally seen as a late-occurring event, growing evidence suggests that this process can begin early during tumor development and the clonal architecture of these tumors is consistently influenced by cancer treatment. Although the survival rate of patients with metastatic CRC patients improved in the last years, the response to current treatments and prognosis of many of these patients remain still poor, indicating the need to discover new improvements for therapeutic vulnerabilities and to formulate a rational prospective of personalized therapies.

Clonal Evolution and Timing of Metastatic Colorectal Cancer

Colorectal cancer (CRC) is the third most frequently diagnosed cancer worldwide, where ~50% of patients develop metastasis, despite current improved management. Genomic characterisation of metastatic CRC, and elucidating the effects of therapy on the metastatic process, are essential to help guide precision medicine. Multi-region whole-exome sequencing was performed on 191 sampled tumour regions of patient-matched therapy-naïve and treated CRC primary tumours (n = 92 tumour regions) and metastases (n = 99 tumour regions), in 30 patients. Somatic variants were analysed to define the origin, composition, and timing of seeding in the metastatic progression of therapy-naïve and treated metastatic CRC. High concordance, with few genomic differences, was observed between primary CRC and metastases. Most cases supported a late dissemination model, via either monoclonal or polyclonal seeding. Polyclonal seeding appeared more common in therapy-naïve metastases than in treated metastases. Whereby, treatment prompted for the selection of distinct resistant clones, through monoclonal seeding to distant metastatic sites. Overall, this study reinforces the importance of early clinical detection and surgical excision of the CRC tumour, whilst further highlighting the clinical challenges for metastatic CRC with increased intratumour heterogeneity (either due to early dissemination or polyclonal metastatic spread) and the underlying risk of future therapeutic resistance in treated patients.

Emerging role of tumor cell plasticity in modifying therapeutic response

Resistance to cancer therapy is a major barrier to cancer management. Conventional views have proposed that acquisition of resistance may result from genetic mutations. However, accumulating evidence implicates a key role of non-mutational resistance mechanisms underlying drug tolerance, the latter of which is the focus that will be discussed here. Such non-mutational processes are largely driven by tumor cell plasticity, which renders tumor cells insusceptible to the drug-targeted pathway, thereby facilitating the tumor cell survival and growth. The concept of tumor cell plasticity highlights the significance of re-activation of developmental programs that are closely correlated with epithelial-mesenchymal transition, acquisition properties of cancer stem cells, and trans-differentiation potential during drug exposure. From observations in various cancers, this concept provides an opportunity for investigating the nature of anticancer drug resistance. Over the years, our understanding of the emerging role of phenotype switching in modifying therapeutic response has considerably increased. This expanded knowledge of tumor cell plasticity contributes to developing novel therapeutic strategies or combination therapy regimens using available anticancer drugs, which are likely to improve patient outcomes in clinical practice.

Curcumin Modifies Epithelial-Mesenchymal Transition in Colorectal Cancer Through Regulation of miR-200c/EPM5

Background

The serious side effect of current conventional treatments for patients with metastatic colorectal cancer (CRC) highlights the requirement of an alternative treatment strategy. Natural compounds, such as curcumin, have been gained much attention due to its low toxicity and anti-tumor effect.

Methods

qPCR and Western blot were used to measure the molecular changes induced by curcumin. Wound-healing assay and transwell assay were conducted to study the effect on cell migration and invasion. RT¹ PCR array was performed to identify the miRNAs involved in curcumin-repressed EMT. Three algorithms and luciferase reporter assay were used to identify EPM5 as a target of miR-200c. The bioinformatical analysis of TCGA-COAD and other CRC cohorts were used to examine the association of EPM5 with EMT signatures and clinical relevance. The ectopic expression or siRNA-mediated knockdown of EPM5 was applied to study the role of EPM5 in CRC.

Results

Treatment with curcumin changed the epithelial–mesenchymal transition (EMT)-related gene expression, repressed cell migration and invasion in CRC cells. Its anti-tumor capability required the upregulation of miR-200c. EPM5 was a direct target of miR-200c and enriched in the consensus molecular subtype (CMS) 4 of CRC. Ectopic expression of EPM5 alone was sufficient to induce EMT in CRC. Downregulation of EPM5 was necessary for curcumin-repressed EMT, migration, and invasion. Higher expression of EPM5 was associated with the advanced TNM stages and poor survival in CRC.

Conclusion

Our data provide the first evidence that the curcumin inhibits EMT in CRC by upregulation of miR-200c and downregulation of EPM5, and the use of curcumin might be able to prevent or delay CRC progression.

Prognostic utility of neutrophil-to-lymphocyte ratio in patients with metastatic colorectal cancer treated using different modalities

Introduction

Inflammation is a critical component in carcinogenesis. The neutrophil-to-lymphocyte ratio (nlr) has been retrospectively studied as a biomarker of prognosis in metastatic colorectal cancer (mcrc). Compared with a low nlr, a high nlr is associated with worse prognosis. In the present study, we compared real-world survival for patients with mcrc based on their nlr group, and we assessed the utility of the nlr in determining first-line chemotherapy and metastasectomy benefit.

Methods

In this retrospective and descriptive analysis of patients with mcrc undergoing first-line chemotherapy in a single centre, the last systemic absolute neutrophil and lymphocyte count before treatment was used for the nlr. A receiver operating characteristic curve was used to estimate the nlr cut-off value, dividing the patients into low and high nlr groups. Median overall survival (mos) was compared using Kaplan-Meier curves and the log-rank test. A multivariate analysis was performed using a Cox regression model.

Results

The 102 analyzed patients had a median follow-up of 15 months. Regardless of systemic therapy, approximately 20% of patients underwent metastasectomy. The nlr cut-off was established at 2.35, placing 45 patients in the low-risk group (nlr < 2.35) and 57 in the high-risk group (nlr ≥ 2.35). The Kaplan-Meier analysis showed a mos of 39.1 months in the low-risk group and 14.4 months in the high-risk group (p < 0.001). Multivariate Cox regression on the nlr estimated a hazard ratio of 3.08 (p = 0.01). Survival analysis in each risk subgroup, considering the history of metastasectomy, was also performed. In the low-risk group, mos was longer for patients undergoing metastasectomy than for those not undergoing the procedure (95.2 months vs. 22.6 months, p = 0.05). In the high-risk group, mos was not statistically different for patients undergoing or not undergoing metastasectomy (24.3 months vs. 12.7 months, p = 0.08).

Conclusions

Our real-world data analysis of nlr in patients with mcrc confirmed that this biomarker is useful in predicting survival. It also suggests that nlr is an effective tool to choose first-line treatment and to predict the benefit of metastasectomy.

Genetic profiling of primary and secondary tumors from patients with lung adenocarcinoma and bone metastases reveals targeted therapy options

Background

Patients newly diagnosed with lung adenocarcinoma with bone metastases (LABM) have poor survival rates after treatment with conventional therapies. To improve outcomes, we retrospectively investigated whether the application of a more comprehensive genetic test of tumor biopsies samples from LABM patients could provide the basis for treatment with more effective tyrosine kinase inhibitors (TKIs) regimens.

Methods

Fine needle biopsies were taken from the primary tumor (PT) and a secondary bone metastasis (BM) of 17 LABM patients before treatment. Simple genetic profiles for selecting therapies were initially obtained using an ARMS-PCR test for EGFR and ALK fusion mutations. More detailed genetic profiles of somatic exon SNVs and CNVs in 457 cancer-related genes were retrospectively derived using capture single molecule amplification and resequencing technology (capSMART).

Results

ARMS-PCR identified 14 EGFR positive, 3 EGFR negative and 1 ALK fusion positive patient. A therapy regimen incorporating TKIs Gefitinib and Crizotinib was offered to the EGFR and ALK fusion positive patients, respectively. With the exception of two patients, molecular profiling of matching PT and BM biopsies identified a highly shared somatic variant fingerprint, although the BMs exhibited additional genomic instability. In six of 13 EGFR positive patients and in all three EGFR negative patients, examination of the genetic profiles identified additional clinically significant mutations that are known or experimental drug targets for treatment of lung cancer.

Conclusion

Our findings firstly suggest that treatment regimens based on comprehensive genetic assessment of newly diagnosed LABM patients should target both the PT and secondary BMs, including rogue clones with potential to form new BMs. Second, the additional information gained should allow clinicians to design and implement more personalized treatment regimens and potentially improve outcomes for LABM patients.

Prophylactical Low Dose Whole-Liver Irradiation Inhibited Colorectal Liver Metastasis by Regulating Hepatic Niche in Mice

Background

The liver is the most common target for metastatic colorectal cancer. Changes of the local hepatic niche due to hepatic diseases such as cirrhosis decrease the incidence of colorectal cancer liver metastasis. Hepatic niche heterogeneity could influence the risk of hepatic metastasis.

Materials and Methods

We simulated changes of the hepatic niche via prophylactical liver irradiation with a safe dose of 6 Gy. GEO dataset and GO analysis revealed a difference in the expression of matrix metalloproteinase 1 (MMP1) in primary colorectal cancer versus liver metastasis, as well as synchronous versus metachronous liver metastasis. Western blotting, Immunofluorescence and qRT-PCR were conducted to measure protein expressions, location and RNA expressions. Colony formation, wound-healing, transwell assays experiments were performed to determine the malignant biological properties of colorectal cancer cells. shRNA transfection was used to conduct stable transfected cell lines.

Results

Tissue inhibitor of metalloproteinases 1 (TIMP1) expression was significantly higher in metastases lesions than primary tumors. In vivo, TIMP1 expression in the hepatic niche increased after a safe dose of 6 Gy irradiation, along with MMP1 decreased, leading to collagen fiber deposition and impairment of hepatic microcirculation. In vitro, irradiated hepatic stellate cells-conditioned media reduced the migration and clone formation ability of colon cancer cells SW480 and HCT116. Low TIMP1 expression in hepatic stellate cells reduced tumor cell invasion and migration.

Conclusion

Prophylactical 6 Gy whole-liver irradiation could inhibit colorectal cancer liver metastasis by regulating TIMP1/MMP1 balance in the hepatic niche before liver metastatic lesion formed.

Artificial Intelligence and Machine Learning in Nuclear Medicine: Future Perspectives

Artificial intelligence and machine learning based approaches are increasingly finding their way into various areas of nuclear medicine imaging. With the technical development of new methods and the expansion to new fields of application, this trend is likely to become even more pronounced in future. Possible means of application range from automated image reading and classification to correlation with clinical outcomes and to technological applications in image processing and reconstruction. In the context of tumor imaging, that is, predominantly FDG or PSMA PET imaging but also bone scintigraphy, artificial intelligence approaches can be used to quantify the whole-body tumor volume, for the segmentation and classification of pathological foci or to facilitate the diagnosis of micro-metastases. More advanced applications aim at the correlation of image features that are derived by artificial intelligence with clinical endpoints, for example, whole-body tumor volume with overall survival. In nuclear medicine imaging of benign diseases, artificial intelligence methods are predominantly used for automated and/or facilitated image classification and clinical decision making. Automated feature selection, segmentation and classification of myocardial perfusion scintigraphy can help in identifying patients that would benefit from intervention and to forecast clinical prognosis. Automated reporting of neurodegenerative diseases such as Alzheimer's disease might be extended to early diagnosis-being of special interest, if targeted treatment options might become available. Technological approaches include artificial intelligence-based attenuation correction of PET images, image reconstruction or anatomical landmarking. Attenuation correction is of special interest for avoiding the need of a coregistered CT scan, in the process of image reconstruction artefacts might be reduced, or ultra low-dose PET images might be denoised. The development of accurate ultra low-dose PET imaging might broaden the method's applicability, for example, toward oncologic PET screening. Most artificial intelligence approaches in nuclear medicine imaging are still in early stages of development, further improvements are necessary for broad clinical applications. In this review, we describe the current trends in the context fields of body oncology, cardiac imaging, and neuroimaging while an additional section puts emphasis on technological trends. Our aim is not only to describe currently available methods, but also to place a special focus on the description of possible future developments.

A persistent high neutrophil-to-lymphocyte ratio predicts poor prognosis in patients with colorectal cancer undergoing resection

The prognostic role of the neutrophil-to-lymphocyte ratio (NLR) has been reported in colorectal cancer (CRC); however, its variation and corresponding predicative value in patients undergoing resection remain largely unknown. In the present study, data from 146 patients with CRC were retrospectively collected, optimal cut-off points for preoperative and postoperative low and high NLRs were set, and ΔNLR was calculated. Subsequently, patients were classified into low-low, low-high, high-low and high-high subgroups based on the cut-off points, and their progression-free survival (PFS) was determined. A Cox proportional hazard model was applied to calculate the prognostic value of all factors. The results demonstrated that both preoperative and postoperative NLRs (pre-NLR and post-NLR) but not ΔNLR could predict PFS with optimal cut-off points of 2.39 and 2.96, respectively. For predicting PFS, the pre-NLR had a sensitivity and specificity of 48.80 and 79.50%, respectively, and the post-NLR had a sensitivity and specificity of 63.20 and 56.20%, respectively. Significant differences were identified between low and high pre-NLRs in terms of histological grade (P<0.01) and tumor diameter (P<0.01); however, such differences were only found in terms of age (P<0.01) for low and high post-NLRs. The PFS of patients in the low-low, low-high, high-low and high-high subgroups was 50.30±21.36, 43.67±22.78, 31.06±25.56 and 29.87±24.13 months, respectively, and patients in the high-high subgroup had the worst PFS (P<0.01). Preoperative CEA level, invasive depth, node involvement, distant metastasis and preoperative NLR were independent prognostic factors. In conclusion, a persistently high NLR for patients with CRC undergoing resection was associated with poor prognosis.

Circulating tumor cell enumeration for improved screening and disease detection of patients with colorectal cancer

Background

The immunochemical fecal occult blood test (iFOBT) for colorectal cancer (CRC) screening and the serum carcinoembryonic antigen (CEA) assay for disease detection of CRC is associated with a high false-positive rate and a low detection sensitivity, respectively. There is an unmet need to define additional modalities to complement these assays. Different subsets of circulating tumor cells (CTCs) are present in the peripheral blood of cancer patients. Whether or not CTCs testing supplements these clinical assays and is valuable for patients with CRC was investigated.

Methods

CTCs were enriched from pre-operative patients with CRC (n = 109) and the non-cancerous controls (n = 65). CTCs expressing either epithelial cell adhesion molecule (EpCAM) or podoplanin (PDPN, the marker associated with poor cancer prognosis) were defined by immunofluorescence staining and were analyzed alone or in combination with iFOBT or serum CEA.

Results

Patients with early or advanced stage of CRC can be clearly identified and differentiated from the non-cancerous controls (p < 0.001) by EpCAM⁺-CTC or PDPN⁺-CTC count. The sensitivity and specificity of EpCAM⁺-CTCs was 85.3% and 78.5%, respectively, when the cutoff value was 23 EpCAM⁺-CTCs/mL of blood; and the sensitivity and specificity of PDPN⁺-CTCs was 78.0% and 75.4%, respectively, when the cutoff value was 7 PDPN⁺-CTCs/mL of blood. Combined analysis of iFOBT with the EpCAM⁺-CTC and PDPN⁺-CTC count reduced the false-positive rate of iFOBT from 56.3% to 18.8% and 23.4%, respectively. Combined analysis of serum CEA with the EpCAM⁺-CTC and PDPN⁺-CTC count increased the disease detection rate from 30.3% to 89.9% and 86.2%, respectively.

Conclusion

CTC testing could supplement iFOBT to improve CRC screening and supplement serum CEA assay for better disease detection of patients with CRC.

Advances and trends of hydrogel therapy platform in localized tumor treatment: A review

Due to limitations of treatment and the stubbornness of infiltrative tumor cells, the outcome of conventional antitumor treatment is often compromised by a variety of factors, including severe side effects, unexpected recurrence, and massive tissue loss during the treatment. Hydrogel-based therapy is becoming a promising option of cancer treatment, because of its controllability, biocompatibility, high drug loading, prolonged drug release, and specific stimuli-sensitivity. Hydrogel-based therapy has good malleability and can reach some areas that cannot be easily touched by surgeons. Furthermore, hydrogel can be used not only as a carrier for tumor treatment agents, but also as a scaffold for tissue repair. In this review, we presented the latest researches in hydrogel applications of localized tumor therapy and highlighted the recent progress of hydrogel-based therapy in preventing postoperative tumor recurrence and improving tissue repair, thus proposing a new trend of hydrogel-based technology in localized tumor therapy. And this review aims to provide a novel reference and inspire thoughts for a more accurate and individualized cancer treatment.

Circulating tumor cells as Trojan Horse for understanding, preventing, and treating cancer: a critical appraisal

Circulating tumor cells (CTCs) are regarded as harbingers of metastases. Their ability to predict response to therapy, relapse, and resistance to treatment has proposed their value as putative diagnostic and prognostic indicators. CTCs represent one of the zeniths of cancer evolution in terms of cell survival; however, the triggers of CTC generation, the identification of potentially metastatic CTCs, and the mechanisms contributing to their heterogeneity and aggressiveness represent issues not yet fully deciphered. Thus, prior to enabling liquid biopsy applications to reach clinical prime time, understanding how the above mechanistic information can be applied to improve treatment decisions is a key challenge. Here, we provide our perspective on how CTCs can provide mechanistic insights into tumor pathogenesis, as well as on CTC clinical value. In doing so, we aim to (a) describe how CTCs disseminate from the primary tumor, and their link to epithelial-mesenchymal transition (EMT); (b) trace the route of CTCs through the circulation, focusing on tumor self-seeding and the possibility of tertiary metastasis; (c) describe possible mechanisms underlying the enhanced metastatic potential of CTCs; (d) discuss how CTC could provide further information on the tissue of origin, especially in cancer of unknown primary origin. We also provide a comprehensive review of meta-analyses assessing the prognostic significance of CTCs, to highlight the emerging role of CTCs in clinical oncology. We also explore how cell-free circulating tumor DNA (ctDNA) analysis, using a combination of genomic and phylogenetic analysis, can offer insights into CTC biology, including our understanding of CTC heterogeneity and tumor evolution. Last, we discuss emerging technologies, such as high-throughput quantitative imaging, radiogenomics, machine learning approaches, and the emerging breath biopsy. These technologies could compliment CTC and ctDNA analyses, and they collectively represent major future steps in cancer detection, monitoring, and management.

Occult Tubal Carcinoma After Risk-Reducing Salpingo-oophorectomy: A Systematic Review

OBJECTIVE

To perform a systematic review of the literature to estimate the prevalence and outcomes of occult tubal carcinoma in BRCA mutation carriers and high-risk patients undergoing risk-reducing salpingo-oophorectomy.

DATA SOURCE

A search was done using OVID MEDLINE, EMBASE, and ClinicalTrials.gov between 1946 and March 2019 with keywords and MeSH terms selected by an expert medical librarian and coauthors.

METHODS OF STUDY SELECTION

Two independent reviewers performed study selection with an initial screen on abstracts and a second on full articles. Articles were rejected if they were irrelevant to the study question, pertained to a different population or did not report occult tubal neoplasia. Quality was assessed using methodologic index for nonrandomized studies criteria.

TABULATION, INTEGRATION, AND RESULTS

Data were extracted and recorded in an Excel database. Forest plots for the prevalence of occult carcinoma were done using STATA. Among 2,402 studies assessed, 27 met the inclusion criteria for qualitative and quantitative analysis. A total of 6,283 patients underwent risk-reducing salpingo-oophorectomy between 2002 and 2019: 2,894 cases were BRCA1, 1,579 BRCA2, and 1,810 high-risk based on family history. Among these, 75 patients were diagnosed with occult tubal carcinoma at the time of surgery. The pooled prevalence was 1.2% (I=7.1%, P=.363) occurring at a median age of 53.2 years (range 42.4-67). In a subanalysis of 18 studies reporting follow-up data, 10 recurrences (18.7%, 95% CI 7.5-53%) and 24 cases of post-risk-reducing salpingo-oophorectomy peritoneal cancer (0.54%, 95% CI 0.4-1.9%) were reported after a median follow-up of 52.5 months. BRCA1, older age, and previous breast cancer were more often associated with occult malignancy.

CONCLUSION

Occult tubal carcinomas found at risk-reducing salpingo-oophorectomy in high-risk patients and BRCA mutation carriers have significant potential for recurrence despite the frequent administration of postoperative chemotherapy.

Intratumor heterogeneity: A new perspective on colorectal cancer research

Colorectal cancers generally consist of multiple subclones. These subclones have their own unique characteristics, resulting in intratumor heterogeneity (ITH). As the discussion of ITH has advanced, a model describing the relationship of ITH to the tumor has gradually emerged. ITH can be divided into two types of intraprimary tumor heterogeneity and intraindividual tumor heterogeneity, the former for further understanding of tumor composition, and the latter for providing more information about evolutionary patterns. With the rapid development of new methods, such as next‐generation, polyguanine region sequencing, and Image detection, researchers may unravel the secrets underlying ITH. The higher the ITH of the tumor, the richer the interaction between the subclones maybe, or the greater the chance of the tumor getting more powerful subclones may be, thus increasing the malignant potential of the tumor. Existing evidence suggests that ITH may increase the ability of tumors to resist treatment and can be used as an independent influence on the prognosis of colorectal cancer. We reviewed 80 recent studies to give researchers a new perspective on colorectal cancer. There is still a limited amount of research in this area. Further study of the relationship between ITH and clinical endpoints may lead to the development of new treatment strategies.

The tumor microenvironment of colorectal cancer metastases: opportunities in cancer immunotherapy

About a fifth of individuals with colorectal cancer (CRC) present with disease metastasis at the time of diagnosis. While the role of the tumor microenvironment (TME) in governing CRC progression is undeniable, the role of the TME in either establishing or suppressing the formation of distant metastases of CRC is less well established. Despite advances in immunotherapy, many individuals with metastatic CRC do not respond to standard-of-care therapy. Therefore, understanding the role of the TME in establishing distant metastases is essential for developing new immunological agents. Here, we summarize our current understanding of the TME of CRC metastases, describe differences between the TME of primary tumors and their distant metastases, and discuss advances in the design and combinations of immunotherapeutic agents.

Relevance Function of Linc-ROR in the Pathogenesis of Cancer

Long non-coding RNAs (lncRNAs) are the key components of non-coding RNAs (ncRNAs) with a length of 200 nucleotides. They are transcribed from the so-called “dark matter” of the genome. Increasing evidence have shown that lncRNAs play an important role in the pathophysiology of human diseases, particularly in the development and progression of tumors. Linc-ROR, as a new intergenic non-protein coding RNA, has been considered to be a pivotal regulatory factor that affects the occurrence and development of human tumors, including breast cancer (BC), colorectal cancer (CRC), pancreatic cancer (PC), hepatocellular carcinoma (HCC), and so on. Dysregulation of Linc-ROR has been closely related to advanced clinicopathological factors predicting a poor prognosis. Because linc-ROR can regulate cell proliferation, apoptosis, migration, and invasion, it can thus be used as a potential biomarker for patients with tumors and has potential clinical significance as a therapeutic target. This article reviewed the role of linc-ROR in the development of tumors, its related molecular mechanisms, and clinical values.

Independent Validation of Early-Stage Non-Small Cell Lung Cancer Prognostic Scores Incorporating Epigenetic and Transcriptional Biomarkers With Gene-Gene Interactions and Main Effects

BACKGROUND

DNA methylation and gene expression are promising biomarkers of various cancers, including non-small cell lung cancer (NSCLC). Besides the main effects of biomarkers, the progression of complex diseases is also influenced by gene-gene (G×G) interactions.

RESEARCH QUESTION

Would screening the functional capacity of biomarkers on the basis of main effects or interactions, using multiomics data, improve the accuracy of cancer prognosis?

STUDY DESIGN AND METHODS

Biomarker screening and model validation were used to construct and validate a prognostic prediction model. NSCLC prognosis-associated biomarkers were identified on the basis of either their main effects or interactions with two types of omics data. A prognostic score incorporating epigenetic and transcriptional biomarkers, as well as clinical information, was independently validated.

RESULTS

Twenty-six pairs of biomarkers with G×G interactions and two biomarkers with main effects were significantly associated with NSCLC survival. Compared with a model using clinical information only, the accuracy of the epigenetic and transcriptional biomarker-based prognostic model, measured by area under the receiver operating characteristic curve (AUC), increased by 35.38% (95% CI, 27.09%-42.17%; P = 5.10 × 10-17) and 34.85% (95% CI, 26.33%-41.87%; P = 2.52 × 10-18) for 3- and 5-year survival, respectively, which exhibited a superior predictive ability for NSCLC survival (AUC3 year, 0.88 [95% CI, 0.83-0.93]; and AUC5 year, 0.89 [95% CI, 0.83-0.93]) in an independent Cancer Genome Atlas population. G×G interactions contributed a 65.2% and 91.3% increase in prediction accuracy for 3- and 5-year survival, respectively.

INTERPRETATION

The integration of epigenetic and transcriptional biomarkers with main effects and G×G interactions significantly improves the accuracy of prognostic prediction of early-stage NSCLC survival.

Molecular and Functional Characterization of Circulating Tumor Cells: From Discovery to Clinical Application

BACKGROUND

One of the objectives for the liquid biopsy is to become a surrogate to tissue biopsies in diagnosis of cancer as a minimally invasive method, with clinical utility in real-time follow-ups of patients. To achieve this goal, it is still necessary to achieve a better understanding of the mechanisms of cancer and the biological principles that govern its behavior, particularly with regard to circulating tumor cells (CTCs).

CONTENT

The isolation, enumeration, detection, and characterization of CTCs have already proven to provide relevant clinical information about patient prognosis and treatment prediction. Moreover, CTCs can be analyzed at the genome, proteome, transcriptome, and secretome levels and can also be used for functional studies in in vitro and in vivo models. These features, taken together, have made CTCs a very valuable biosource.

SUMMARY

To further advance the field and discover new clinical applications for CTCs, several studies have been performed to learn more about these cells and better understand the biology of metastasis. In this review, we describe the recent literature on the topic of liquid biopsy with particular focus on the biology of CTCs.

Src Family Tyrosine Kinases in Intestinal Homeostasis, Regeneration and Tumorigenesis

Src, originally identified as an oncogene, is a membrane-anchored tyrosine kinase and the Src family kinase (SFK) prototype. SFKs regulate the signalling induced by a wide range of cell surface receptors leading to epithelial cell growth and adhesion. In the intestine, the SFK members Src, Fyn and Yes regulate epithelial cell proliferation and migration during tissue regeneration and transformation, thus implicating conserved and specific functions. In patients with colon cancer, SFK activity is a marker of poor clinical prognosis and a potent driver of metastasis formation. These tumorigenic activities are linked to SFK capacity to promote the dissemination and tumour-initiating capacities of epithelial tumour cells. However, it is unclear how SFKs promote colon tumour formation and metastatic progression because SFK-encoding genes are unfrequently mutated in human cancer. Here, we review recent findings on SFK signalling during intestinal homeostasis, regeneration and tumorigenesis. We also describe the key nongenetic mechanisms underlying SFK tumour activities in colorectal cancer, and discuss how these mechanisms could be exploited in therapeutic strategies to target SFK signalling in metastatic colon cancer.

The Metastatic Cascade as the Basis for Liquid Biopsy Development

The metastatic cascade describes the process whereby aggressive cancer cells leave the primary tumor, travel through the bloodstream, and eventually reach distant organs to develop one or several metastases. During the last decade, innovative technologies have exploited the recent biological knowledge to identify new circulating biomarkers for the screening and early detection of cancer, real-time monitoring of treatment response, assessment of tumor relapse risk (prognosis), identification of new therapeutic targets and resistance mechanisms, patient stratification, and therapeutic decision-making. These techniques are broadly described using the term of Liquid Biopsy. This field is in constant progression and is based on the detection of circulating tumor cells, circulating free nucleic acids (e.g., circulating tumor DNA), circulating tumor-derived extracellular vesicles, and tumor-educated platelets. The aim of this review is to describe the biological principles underlying the liquid biopsy concept and to discuss how functional studies can expand the clinical applications of these circulating biomarkers.

Recurrent Neoantigens in Colorectal Cancer as Potential Immunotherapy Targets

This study was aimed at investigating the mutations in colorectal cancer (CRC) for recurrent neoantigen identification. A total of 1779 samples with whole exome sequencing (WES) data were obtained from 7 published CRC cohorts. Common HLA genotypes were used to predict the probability of neoantigens at high-frequency mutants in the dataset. Based on the WES data, we not only obtained the most comprehensive CRC mutation landscape so far but also found 1550 mutations which could be identified in at least 5 patients, including KRAS G12D (8%), KRAS G12V (5.8%), PIK3CA E545K (3.5%), PIK3CA H1047R (2.5%), and BMPR2 N583Tfs∗44 (2.8%). These mutations can also be recognized by multiple common HLA molecules in Chinese and TCGA cohort as potential "public" neoantigens. Many of these mutations also have high mutation rates in metastatic pan-cancers, suggesting their value as therapeutic targets in different cancer types. Overall, our analysis provides recurrent neoantigens as potential cancer immunotherapy targets.

Combinatorial Immunotherapies for Metastatic Colorectal Cancer

Colorectal cancer (CRC) is one of the most frequent and deadly forms of cancer. About half of patients are affected by metastasis, with the cancer spreading to e.g., liver, lungs or the peritoneum. The majority of these patients cannot be cured despite steady advances in treatment options. Immunotherapies are currently not widely applicable for this disease, yet show potential in preclinical models and clinical translation. The tumour microenvironment (TME) has emerged as a key factor in CRC metastasis, including by means of immune evasion-forming a major barrier to effective immuno-oncology. Several approaches are in development that aim to overcome the immunosuppressive environment and boost anti-tumour immunity. Among them are vaccination strategies, cellular transplantation therapies, and targeted treatments. Given the complexity of the system, we argue for rational design of combinatorial therapies and consider the implications of precision medicine in this context.

Epigenetic plasticity in metastatic dormancy: mechanisms and therapeutic implications

The overwhelming majority of cancer-associated morbidity and mortality can be ascribed to metastasis. Metastatic disease frequently presents in a delayed fashion following initial diagnosis and treatment, requiring that disseminated cancer cells (DCCs) spread early in tumor progression and persist in a dormant state at metastatic sites. To accomplish this feat, DCCs exhibit substantial phenotypic plasticity that is mediated by the epigenetic regulation of dormancy programs in response to intrinsic (i.e., cellular) and extrinsic (i.e., microenvironmental) cues. The epigenome is a dynamic landscape that encompasses transcriptional regulation via alteration of chromatin architecture, posttranscriptional RNA processing, and the diverse functions carried out by noncoding RNAs. Signals converging on DCCs are transduced through epigenetic effectors. Conversely, epigenetic regulation of gene expression controls the crosstalk between DCCs and cells of the metastatic niche, a phenomenon that is essential for the institution of dormant phenotypes. Importantly, epigenetic effectors can be targeted therapeutically, and the development of novel epigenetic therapies may provide new inroads to combating recurrent metastatic disease. Here we provide an overview of the dynamics of metastatic dormancy and summarize our current understanding of the intersections between dormancy and the epigenome, both mechanistically and therapeutically.

The dormant cancer cell life cycle

The success of targeted therapies and immunotherapies has created optimism that cancers may be curable. However, not all patients respond, drug resistance is common and many patients relapse owing to dormant cancer cells. These rare and elusive cells can disseminate early and hide in specialized niches in distant organs before being reactivated to cause disease relapse after successful treatment of the primary tumour. Despite their importance, we are yet to leverage knowledge generated from experimental models and translate the potential of targeting dormant cancer cells to prevent disease relapse in the clinic. This is due, at least in part, to the lack of adherence to consensus definitions by researchers, limited models that faithfully recapitulate this stage of metastatic spread and an absence of interdisciplinary approaches. However, the application of new high-resolution, single-cell technologies is starting to revolutionize the field and transcend classical reductionist models of studying individual cell types or genes in isolation to provide a global view of the complex underlying cellular ecosystem and transcriptional landscape that controls dormancy. In this Perspective, we synthesize some of these recent advances to describe the hallmarks of cancer cell dormancy and how the dormant cancer cell life cycle offers opportunities to target not only the cancer but also its environment to achieve a durable cure for seemingly incurable cancers.

Navigating the path to distant metastasis

How ‘difficult’ is it for somatic evolution to produce a cell that is capable of leaving the primary tumor and growing in a distant organ? In this issue, Reiter et al. assess genetic diversity across metastatic lesions and identify a tight selective bottleneck preceding distant metastasis.

Looking backward in time to define the chronology of metastasis

The timing of cancer metastasis has implications for treatment and prevention. Traditional forward-time views of metastasis assume it occurs late during evolution. However, looking backward in time reveals metastasis often occurs prior to clinical detection of primary tumors.

Visualizing Human Colorectal Cancer Intratumor Heterogeneity with Phylogeography

Phylogeography combines ancestry with location and can be translated to intratumor heterogeneity (ITH) to visualize how tumors spread. ITH is common in human tumors, with many genetic and phenotypic differences between regions. The roles of ITH in progression are uncertain because many subclones lack discernable driver mutations. ITH can be visualized by mapping mutations onto microscopic sections, where subclones are directly associated with phenotypes, especially the deeper areas with the more invasive cells that confer worst clinical outcomes. Instead of a stepwise hierarchy where subclones segregate by phenotype with later branching subclones in more invasive areas, multiple subclones share superficial and invasive phenotype and are jigsaw arrayed in vertical columns. Phylogeography shows that both early and late subclones extend from the surface to the invasive front, suggesting that founder cells start with phenotypic plasticity and essentially all the drivers necessary to rapidly grow into large invasive tumors.

Perioperative COX2 and β-adrenergic blockade improves biomarkers of tumor metastasis, immunity, and inflammation in colorectal cancer: A randomized controlled trial

BACKGROUND

Preclinical studies have implicated excess release of catecholamines and prostaglandins in the mediation of prometastatic processes during surgical treatment of cancer. In this study, we tested the combined perioperative blockade of these pathways in patients with colorectal cancer (CRC).

METHODS

In a randomized, double-blind, placebo-controlled biomarker trial involving 34 patients, the β-blocker propranolol and the COX2-inhibitor etodolac were administered for 20 perioperative days, starting 5 days before surgery. Excised tumors were subjected to whole genome messenger RNA profiling and transcriptional control pathway analyses.

RESULTS

Drugs were well-tolerated, with minor complications in both the treatment group and the placebo group. Treatment resulted in a significant improvement (P < .05) of tumor molecular markers of malignant and metastatic potential, including 1) reduced epithelial-to-mesenchymal transition, 2) reduced tumor infiltrating CD14⁺ monocytes and CD19⁺ B cells, and 3) increased tumor infiltrating CD56⁺ natural killer cells. Transcriptional activity analyses indicated a favorable drug impact on 12 of 19 a priori hypothesized CRC-related transcription factors, including the GATA, STAT, and EGR families as well as the CREB family that mediates the gene regulatory impact of β-adrenergic- and prostaglandin-signaling. Alterations observed in these transcriptional activities were previously associated with improved long-term clinical outcomes. Three-year recurrence rates were assessed for long-term safety analyses. An intent-to-treat analysis revealed that recurrence rates were 12.5% (2/16) in the treatment group and 33.3% (6/18) in the placebo group (P = .239), and in protocol-compliant patients, recurrence rates were 0% (0/11) in the treatment group and 29.4% (5/17) in the placebo group (P = .054).

CONCLUSIONS

The favorable biomarker impacts and clinical outcomes provide a rationale for future randomized placebo-controlled trials in larger samples to assess the effects of perioperative propranolol/etodolac treatment on oncological clinical outcomes.

Liver regeneration and liver metastasis

Surgical resection for primary and secondary hepatic neoplasms provides the best chance of cure. Advanced surgical techniques such as portal vein embolisation, two-staged hepatectomy and associated liver partition and portal vein ligation for staged-hepatectomy (ALPPS) have facilitated hepatic resection in patients with previously unresectable, bi-lobar disease. These techniques are frequently employed to ensure favourable clinical outcomes and avoid potentially fatal post-operative complications such as small for size syndrome and post-hepatectomy liver failure. However, they rely on the innate ability of the liver to regenerate. As our knowledge of liver organogenesis, liver regeneration and hepatocarcinogenesis has expanded in recent decades it has come to light that liver regeneration may also drive tumour recurrence. Clinical studies in patients undergoing portal vein embolisation indicate that tumours may progress following the procedure in concordance with liver regeneration and hypertrophy, however overall survival in these patients has not been shown to be worse. In this article, we delve into the mechanisms underlying liver regeneration to better understand the complex ways in which this may affect tumour behaviour and ultimately inform clinical decisions.

Omics Integration Analyses Reveal the Early Evolution of Malignancy in Breast Cancer

The majority of cancer evolution studies involve individual-based approaches that neglect the population dynamics necessary to build a global picture of cancer evolution for each cancer type. Here, we conducted a population-based study in breast cancer to understand the timing of malignancy evolution and its correlation to the genetic evolution of pathological stages. In an omics integrative approach, we integrated gene expression and genomic aberration data for pre-invasive (ductal carcinoma in situ; DCIS, early-stage) and post-invasive (invasive ductal carcinoma; IDC, late-stage) samples and investigated the evolutionary role of further genetic changes in later stages compared to the early ones. We found that single gene alterations (SGAs) and copy-number alterations (CNAs) work together in forward and backward evolution manners to fine-tune the signaling pathways operating in tumors. Analyses of the integrated point mutation and gene expression data showed that (i) our proposed fine-tuning concept is also applicable to metastasis, and (ii) metastases sometimes diverge from the primary tumor at the DCIS stage. Our results indicated that the malignant potency of breast tumors is constant over the pre- and post-invasive pathological stages. Indeed, further genetic alterations in later stages do not establish de novo malignancy routes; however, they serve to fine-tune antecedent signaling pathways.