The challenges of tumor genetic diversity

Recent advances on quinoxalines as target-oriented chemotherapeutic anticancer agents through apoptosis

The current review outlines all possible recent synthetic platforms to quinoxaline derivatives and the potent stimulated apoptosis mechanisms targeted by anticancer therapies. The currently reported results disclosed that quinoxaline derivatives had promising anticancer potencies against a wide array of cancer cell lines, better than the reference drugs, through target inhibition. This review summarizes some potent quinoxaline derivatives with their synthesis strategies and their potential activities against various molecular targets. Quinoxalines can be considered an important scaffold for apoptosis inducers in cancer cells through inhibiting some molecular targets, so they can be further developed as target-oriented chemotherapeutics.

Recent progress in combination therapy of oncolytic vaccinia virus

In recent years, oncolytic viruses have emerged as promising agents for treating various cancers. An oncolytic virus is a non-pathogenic virus that, due to genetic manipulation, tends to replicate in and cause lysis of cancerous cells while leaving healthy cells unaffected. Among these viruses, vaccinia virus is an attractive platform for use as an oncolytic platform due to its 190 Kb genome with a high capacity for encoding therapeutic payloads. Combining oncolytic VV therapy with other conventional cancer treatments has been shown to be synergistic and more effective than monotherapies. Additionally, OVV can be used as a vector to deliver therapeutic payloads, alone or in combination with other treatments, to increase overall efficacy. Here, we present a comprehensive analysis of preclinical and clinical studies that have evaluated the efficacy of oncolytic vaccinia viruses in cancer immunotherapy. We discuss the outcomes of these studies, including tumor regression rates, overall survival benefits, and long-term responses. Moreover, we provide insights into the challenges and limitations associated with oncolytic vaccinia virus- based therapies, including immune evasion mechanisms, potential toxicities, and the development of resistance.

Clinical implication of genetic intratumor heterogeneity for targeted therapy in head and neck cancer

BACKGROUND

Genomic profiling is increasingly used both in therapeutic decision-making and as inclusion criteria for trials testing targeted therapies. However, the mutational landscape may vary across different areas of a tumor and intratumor heterogeneity will challenge treatments or clinical decisions based on single tumor biopsies. The purpose of this study was to assess the clinical relevance of genetic intratumor heterogeneity in head and neck squamous cell carcinomas (HNSCC) using the ESMO Scale for Clinical Actionability of Molecular Targets (ESCAT).

MATERIALS AND METHODS

This prospective study included 33 whole tumor specimens from 28 patients with primary or recurrent HNSCC referred for surgery. Three tumor blocks were selected from central, semi-peripheral, and peripheral positions, mimicking biopsies in three different locations. Genetic analysis of somatic copy number alterations (SCNAs) was performed on the three biopsies using Oncoscan, focusing on 45 preselected HNSCC genes of interest. Clinical relevance was assessed using the ESCAT score to investigate whether and how treatment decisions would change based on the three biopsies from the same tumor.

RESULTS

The SCNAs identified among 45 preselected genes within the three tumor biopsies derived from the same tumor revealed distinct variations. The detected discrepancies could potentially influence treatment approaches or clinical decisions in 36% of the patients if only one tumor biopsy was used. Recurrent tumors exhibited significantly higher variation in SCNAs than primary tumors (p = .024). No significant correlation between tumor size and heterogeneity (p = .7) was observed.

CONCLUSION

In 36% of patients diagnosed with HNSCC, clinically significant intratumor heterogeneity was observed which may have implications for patient management. This finding substantiates the need for future studies that specifically investigate the clinical implications associated with intratumor heterogeneity.

Comparative bioinformatic analysis of KRAS, STK11 and KEAP1 (co-)mutations in non-small cell lung cancer with a special focus on KRAS G12C

OBJECTIVES

Mutations in STK11 (STK11MUT) and KEAP1 (KEAP1MUT) occur frequently in non-small cell lung cancer (NSCLC) and are often co-mutated with KRAS. Several studies linked the co-occurrence of KRASMUT + STK11MUT, as well as KRASMUT + KEAP1MUT to reduced response to immune checkpoint inhibitors (ICI) and even a negative impact on survival. Data focusing STK11 + KEAP1 co-mutations or the triple mutation (KRAS + STK11 + KEAP1) are scarce. The recent availability of KRAS-G12C inhibitors increases the clinical relevance of those co-mutations in KRAS-mutated NSCLC.

MATERIALS AND METHODS

We present a comprehensive bioinformatic analysis encompassing six datasets retrieved from cBioPortal.

RESULTS

Independent of the treatment, triple mutations and STK11MUT + KEAP1MUT were significantly associated with a reduced overall survival (OS). Across treatments, OS of patients with a KRAS G12C triple mutation was significantly reduced compared to patients with KRAS G12C-only. Under ICI-therapy, there was no significant difference in OS between patients harboring the KRAS G12C-only and patients with the KRAS G12C triple mutation, but a significant difference between patients harboring KRAS non-G12C and KRAS non-G12C triple mutations. Triple mutated primary tumors showed a significantly increased frequency of distant metastases to bone and adrenal glands compared to KRAS-only mutated tumors. Additionally, our drug response analysis in cancer cell lines harboring the triple mutations revealed the WNT pathway inhibitor XAV-939 as a potential future drug candidate for this mutational situation.

CONCLUSION

The triple mutation status may serve as a negative prognostic and predictive factor across treatments compared to KRASMUT-only. KRAS G12C generally seems to be a negative predictive marker for ICI-therapy.

Impact of Opioids on Cellular Metabolism: Implications for Metabolic Pathways Involved in Cancer

Opioid utilization for pain management is prevalent among cancer patients. There is significant evidence describing the many effects of opioids on cancer development. Despite the pivotal role of metabolic reprogramming in facilitating cancer growth and metastasis, the specific impact of opioids on crucial oncogenic metabolic pathways remains inadequately investigated. This review provides an understanding of the current research on opioid-mediated changes to cellular metabolic pathways crucial for oncogenesis, including glycolysis, the tricarboxylic acid cycle, glutaminolysis, and oxidative phosphorylation (OXPHOS). The existing literature suggests that opioids affect energy production pathways via increasing intracellular glucose levels, increasing the production of lactic acid, and reducing ATP levels through impediment of OXPHOS. Opioids modulate pathways involved in redox balance which may allow cancer cells to overcome ROS-mediated apoptotic signaling. The majority of studies have been conducted in healthy tissue with a predominant focus on neuronal cells. To comprehensively understand the impact of opioids on metabolic pathways critical to cancer progression, research must extend beyond healthy tissue and encompass patient-derived cancer tissue, allowing for a better understanding in the context of the metabolic reprogramming already undergone by cancer cells. The current literature is limited by a lack of direct experimentation exploring opioid-induced changes to cancer metabolism as they relate to tumor growth and patient outcome.

Cancer chemotherapy and beyond: Current status, drug candidates, associated risks and progress in targeted therapeutics

Cancer is an abnormal state of cells where they undergo uncontrolled proliferation and produce aggressive malignancies that causes millions of deaths every year. With the new understanding of the molecular mechanism(s) of disease progression, our knowledge about the disease is snowballing, leading to the evolution of many new therapeutic regimes and their successive trials. In the past few decades, various combinations of therapies have been proposed and are presently employed in the treatment of diverse cancers. Targeted drug therapy, immunotherapy, and personalized medicines are now largely being employed, which were not common a few years back. The field of cancer discoveries and therapeutics are evolving fast as cancer type-specific biomarkers are progressively being identified and several types of cancers are nowadays undergoing systematic therapies, extending patients' disease-free survival thereafter. Although growing evidence shows that a systematic and targeted approach could be the future of cancer medicine, chemotherapy remains a largely opted therapeutic option despite its known side effects on the patient's physical and psychological health. Chemotherapeutic agents/pharmaceuticals served a great purpose over the past few decades and have remained the frontline choice for advanced-stage malignancies where surgery and/or radiation therapy cannot be prescribed due to specific reasons. The present report succinctly reviews the existing and contemporary advancements in chemotherapy and assesses the status of the enrolled drugs/pharmaceuticals; it also comprehensively discusses the emerging role of specific/targeted therapeutic strategies that are presently being employed to achieve better clinical success/survival rate in cancer patients.

Non-pharmacologic interventions for improving cancer-related fatigue (CRF): A systematic review of systematic reviews and pooled meta-analysis

INTRODUCTION

Literature encloses numerous systematic reviews (SRs) on nonpharmacologic interventions for improving cancer-related fatigue (CRF). The effect of these interventions remains controversial, and the available SRs have not been synthesized yet. We conducted a systematic synthesis of SRs and meta-analysis to determine the effect of nonpharmacologic interventions on CRF in adults.

MATERIAL AND METHODS

We systematically searched 4 databases. The effect sizes (standard mean difference) were quantitatively pooled using a random-effects model. Chi-squared (Q) and I-square statistics (I²) tested the heterogeneity.

RESULTS

We selected 28 SRs, including 35 eligible meta-analyses. The pooled effect size (standard mean difference, 95% CI) was -0.67 (-1.16, -0.18). The subgroup analysis by types of interventions showed a significant effect in all the investigated approaches (complementary integrative medicine, physical exercise, self-management/e-health interventions).

CONCLUSIONS

There is evidence that nonpharmacologic interventions are associated with CRF reduction. Future research should focus on testing these interventions on specific population clusters and trajectories.

PROSPERO REGISTRATION

CRD42020194258.

Cell Adaptive Fitness and Cancer Evolutionary Dynamics

Genome instability of cancer cells translates into increased entropy and lower information processing capacity, leading to metabolic reprograming toward higher energy states, presumed to be aligned with a cancer growth imperative. Dubbed as the cell adaptive fitness, the proposition postulates that the coupling between cell signaling and metabolism constrains cancer evolutionary dynamics along trajectories privileged by the maintenance of metabolic sufficiency for survival. In particular, the conjecture postulates that clonal expansion becomes restricted when genetic alterations induce a sufficiently high level of disorder, that is, high entropy, in the regulatory signaling network, abrogating as a result the ability of cancer cells to successfully replicate, leading to a stage of clonal stagnation. The proposition is analyzed in the context of an in-silico model of tumor evolutionary dynamics to illustrate how cell-inherent adaptive fitness may predictably constrain clonal evolution of tumors, which would have significant implications for the design of adaptive cancer therapies.

Antitumoral Activity of Leptocarpha rivularis Flower Extracts against Gastric Cancer Cells

Leptocarpha rivularis is a native South American plant used ancestrally by Mapuche people to treat gastrointestinal ailments. L. rivularis flower extracts are rich in molecules with therapeutic potential, including the sesquiterpene lactone leptocarpin, which displays cytotoxic effects against various cancer types in vitro. However, the combination of active molecules in these extracts could offer a hitherto unexplored potential for targeting cancer. In this study, we investigated the effect of L. rivularis flower extracts on the proliferation, survival, and spread parameters of gastric cancer cells in vitro. Gastric cancer (AGS and MKN-45) and normal immortalized (GES-1) cell lines were treated with different concentrations of L. rivularis flower extracts (DCM, Hex, EtOAc, and EtOH) and we determined the changes in proliferation (MTS assay, cell cycle analysis), cell viability/cytotoxicity (trypan blue exclusion assay, DEVDase activity, mitochondrial membrane potential MMP, and clonogenic ability), senescence (β-galactosidase activity) and spread potential (invasion and migration assays using the Boyden chamber approach) in all these cells. The results showed that the DCM, EtOAc, and Hex extracts display a selective antitumoral effect in gastric cancer cells by affecting all the cancer parameters tested. These findings reveal an attractive antitumoral potential of L. rivularis flower extracts by targeting several acquired capabilities of cancer cells.

Hypoxia-Inducible Factors-Based Single Nucleotide Polymorphism in Breast Cancer with More Cancer Susceptibility

Hypoxia-inducible factors (HIFs) are a collection of transcriptional factors that engage in the regulation of oxygen homeostasis. They are hypoxia-responsive stress factors whose expression is linked to tumor growth and angiogenesis. HIF is a crucial player in the progression of breast cancer. Patients with high levels of hypoxia-inducible HIFs in their primary tumor biopsies had a higher chance of metastasis, the leading cause of breast cancer-related death. HIF polymorphisms have been shown in several epidemiological studies to influence breast cancer susceptibility. In the oxygendependent degradation domain, several short nucleotide polymorphisms (SNPs) of the HIF gene have been connected with higher HIF activity. To find SNP that make up the genetic diversity that underpins the phenotypic difference found between individuals in their susceptibility to cancer and the course of their disease, researchers used a variety of potential pathway-based approaches.

Programmatic Precision Oncology Decision Support for Patients With Gastrointestinal Cancer

PURPOSE

With the growing number of available targeted therapeutics and molecular biomarkers, the optimal care of patients with cancer now depends on a comprehensive understanding of the rapidly evolving landscape of precision oncology, which can be challenging for oncologists to navigate alone.

METHODS

We developed and implemented a precision oncology decision support system, GI TARGET, (Gastrointestinal Treatment Assistance Regarding Genomic Evaluation of Tumors) within the Gastrointestinal Cancer Center at the Dana-Farber Cancer Institute. With a multidisciplinary team, we systematically reviewed tumor molecular profiling for GI tumors and provided molecularly informed clinical recommendations, which included identifying appropriate clinical trials aided by the computational matching platform MatchMiner, suggesting targeted therapy options on or off the US Food and Drug Administration-approved label, and consideration of additional or orthogonal molecular testing.

RESULTS

We reviewed genomic data and provided clinical recommendations for 506 patients with GI cancer who underwent tumor molecular profiling between January and June 2019 and determined follow-up using the electronic health record. Summary reports were provided to 19 medical oncologists for patients with colorectal (n = 198, 39%), pancreatic (n = 124, 24%), esophagogastric (n = 67, 13%), biliary (n = 40, 8%), and other GI cancers. We recommended ≥ 1 precision medicine clinical trial for 80% (406 of 506) of patients, leading to 24 enrollments. We recommended on-label and off-label targeted therapies for 6% (28 of 506) and 25% (125 of 506) of patients, respectively. Recommendations for additional or orthogonal testing were made for 42% (211 of 506) of patients.

CONCLUSION

The integration of precision medicine in routine cancer care through a dedicated multidisciplinary molecular tumor board is scalable and sustainable, and implementation of precision oncology recommendations has clinical utility for patients with cancer.

Mass Spectrometry-Based Chemical Proteomics for Drug Target Discoveries

Chemical proteomics, emerging rapidly in recent years, has become a main approach to identifying interactions between the small molecules and proteins in the cells on a proteome scale and mapping the signaling and/or metabolic pathways activated and regulated by these interactions. The methods of chemical proteomics allow not only identifying proteins targeted by drugs, characterizing their toxicity and discovering possible off-target proteins, but also elucidation of the fundamental mechanisms of cell functioning under conditions of drug exposure or due to the changes in physiological state of the organism itself. Solving these problems is essential for both basic research in biology and clinical practice, including approaches to early diagnosis of various forms of serious diseases or prediction of the effectiveness of therapeutic treatment. At the same time, recent developments in high-resolution mass spectrometry have provided the technology for searching the drug targets across the whole cell proteomes. This review provides a concise description of the main objectives and problems of mass spectrometry-based chemical proteomics, the methods and approaches to their solution, and examples of implementation of these methods in biomedical research.

The Evolution of BRAF Activation in Non-Small-Cell Lung Cancer

Non-small-cell lung cancer (NSCLC) is the most common subtype of lung cancer, of which approximate 4% had BRAF activation, with an option for targeted therapy. BRAF activation comprises of V600 and non-V600 mutations, fusion, rearrangement, in-frame deletions, insertions, and co-mutations. In addition, BRAF primary activation and secondary activation presents with different biological phenotypes, medical senses and subsequent treatments. BRAF primary activation plays a critical role in proliferation and metastasis as a driver gene of NSCLC, while secondary activation mediates acquired resistance to other targeted therapy, especially for epidermal growth factor tyrosine kinase inhibitor (EGFR-TKI). Treatment options for different activation of BRAF are diverse. Targeted therapy, especially two-drug combination therapy, is an important option. Besides, immune checkpoint inhibitors (ICIs) would be another option since BRAF activation would be a positive biomarker of tumor response of ICIs therapy. To date, no high level evidences support targeted therapy or immunotherapy as prioritized recommendation. After targeted therapy, the evolution of BRAF includes the activation of the upstream, downstream and bypass pathways of BRAF. In this review, therapeutic modalities and post-therapeutic evolutionary pathways of BRAF are discussed, and future research directions are also provided.

PTEN/AKT signaling pathway related to hTERT downregulation and telomere shortening induced in Toxoplasma GRA16-expressing colorectal cancer cells

This study investigated whether the molecular mechanism of granule protein 16 (GRA16), a dense granule protein of Toxoplasma gondii (T. gondii) that induces cancer cell apoptosis, results in telomere shortening in cancer cells. The molecular mechanism of GRA16 responsible for regulating telomerase reverse transcriptase (hTERT) activity and telomere shortening was investigated using GRA16-transferred HCT116 human colorectal cancer cells (GRA16-stable cells). GRA16 directly decreased hTERT expression by downregulating the expression and phosphorylation of hTERT transcriptional factors accompanied by decreased expression of shelterin complex molecules. Moreover, GRA16 resulted in cancer cell death through reduction of telomerase activity which leads to telomere shortening (decreased relative ratio of telomeric repeat-amplified sequence to that of a single-copy gene) (T/S ratio)), and at the same time gamma-H2A histone family member X (γ-H2A.X) stained nucleus was increased in the cells. The molecular mechanism between GRA16 and hTERT inactivation was revealed using inhibitors for phosphatase and tensin homolog (PTEN) and protein phosphatase 2A (PP2A) as well as siRNAs against PTEN and PP2A. hTERT dephosphorylation was induced effectively by the signaling pathway of HAUSP/PTEN/p-AKT(S473) but not by PP2A-B55/p-AKT(T308). Inhibition of the PTEN signaling pathway increased mRNA expressions in hTERT transcriptional factors, cell cycle activating factors, and apoptosis-inhibiting factors. When HCT116 cells were infected with T. gondii, the number of γ-H2A.X-stained nuclei also increased and p-hTERT/hTERT decreased as in GRA16-stable cells. Altogether, our results emphasize that GRA16 is a novel promising telomerase inhibitor that causes telomere shortening through telomerase inactivation by inducing the activation of the tumor suppressor PTEN.

The Zebrafish model in dermatology: an update for clinicians

Recently, the zebrafish has been established as one of the most important model organisms for medical research. Several studies have proved that there is a high level of similarity between human and zebrafish genomes, which encourages the use of zebrafish as a model for understanding human genetic disorders, including cancer. Interestingly, zebrafish skin shows several similarities to human skin, suggesting that this model organism is particularly suitable for the study of neoplastic and inflammatory skin disorders. This paper appraises the specific characteristics of zebrafish skin and describes the major applications of the zebrafish model in dermatological research.

A sheet pocket to prevent cross-contamination of formalin-fixed paraffin-embedded block for application in next generation sequencing

Formalin-fixed paraffin-embedded (FFPE) blocks are used as biomaterials for next-generation sequencing of cancer panels. Cross-contamination is detected in approximately 5% of the DNA extracted from FFPE samples, which reduces the detection rate of genetic abnormalities. There are no effective methods available for processing FFPE blocks that prevent cells from mixing with other specimens. The present study evaluated 897 sheets that could potentially prevent cell transmission but allow for the movement of various solvents used in FFPE blocks. According to the International Organization for Standardization and Japanese Industrial Standards, six requirements were established for the screening of packing sheets: 1) filter opening ≤5 μm, 2) thickness ≤100 μm, 3) chemical resistance, 4) permeability ≥1.0 × 10⁻³ cm/s, 5) water retention rate <200%, and 6) cell transit test (≤2 cells/10 high-power fields). Polyamide, polyethylene terephthalate, and polypropylene/polyethylene composite sheets met all criteria. A pocket, which was designed to wrap the tissue uniformly, was made of these sheets and was found to effectively block the entry of all cell types during FFPE block processing. Using a sheet pocket, no single cell from the cell pellet could pass through the outer layer. The presence or absence of the sheet pocket did not affect hematoxylin and eosin staining. When processing FFPE blocks as a biomaterial for next-generation sequencing, the sheet pocket was effective in preventing cross-contamination. This technology will in part support the precise translation of histopathological data into genome sequencing data in general pathology laboratories.

Serial monitoring of genomic alterations in circulating tumor cells of ER-positive/HER2-negative advanced breast cancer: feasibility of precision oncology biomarker detection

Nearly all estrogen receptor (ER)-positive (POS) metastatic breast cancers become refractory to endocrine (ET) and other therapies, leading to lethal disease presumably due to evolving genomic alterations. Timely monitoring of the molecular events associated with response/progression by serial tissue biopsies is logistically difficult. Use of liquid biopsies, including circulating tumor cells (CTC) and circulating tumor DNA (ctDNA), might provide highly informative, yet easily obtainable, evidence for better precision oncology care. Although ctDNA profiling has been well investigated, the CTC precision oncology genomic landscape and the advantages it may offer over ctDNA in ER-POS breast cancer remain largely unexplored. Whole-blood (WB) specimens were collected at serial time points from patients with advanced ER-POS/HER2-negative (NEG) advanced breast cancer in a phase I trial of AZD9496, an oral selective ER degrader (SERD) ET. Individual CTC were isolated from WB using tandem CellSearch® /DEPArray™ technologies and genomically profiled by targeted single-cell DNA next-generation sequencing (scNGS). High-quality CTC (n = 123) from 12 patients profiled by scNGS showed 100% concordance with ctDNA detection of driver estrogen receptor α (ESR1) mutations. We developed a novel CTC-based framework for precision medicine actionability reporting (MI-CTCseq) that incorporates novel features, such as clonal predominance and zygosity of targetable alterations, both unambiguously identifiable in CTC compared to ctDNA. Thus, we nominated opportunities for targeted therapies in 73% of patients, directed at alterations in phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA), fibroblast growth factor receptor 2 (FGFR2), and KIT proto-oncogene, receptor tyrosine kinase (KIT). Intrapatient, inter-CTC genomic heterogeneity was observed, at times between time points, in subclonal alterations. Our analysis suggests that serial monitoring of the CTC genome is feasible and should enable real-time tracking of tumor evolution during progression, permitting more combination precision medicine interventions.

Knowledge graph-based recommendation framework identifies drivers of resistance in EGFR mutant non-small cell lung cancer

Resistance to EGFR inhibitors (EGFRi) presents a major obstacle in treating non-small cell lung cancer (NSCLC). One of the most exciting new ways to find potential resistance markers involves running functional genetic screens, such as CRISPR, followed by manual triage of significantly enriched genes. This triage process to identify ‘high value’ hits resulting from the CRISPR screen involves manual curation that requires specialized knowledge and can take even experts several months to comprehensively complete. To find key drivers of resistance faster we build a recommendation system on top of a heterogeneous biomedical knowledge graph integrating pre-clinical, clinical, and literature evidence. The recommender system ranks genes based on trade-offs between diverse types of evidence linking them to potential mechanisms of EGFRi resistance. This unbiased approach identifies 57 resistance markers from >3,000 genes, reducing hit identification time from months to minutes. In addition to reproducing known resistance markers, our method identifies previously unexplored resistance mechanisms that we prospectively validate.

Resistance to EGFR inhibitors presents a major obstacle in treating non-small cell lung cancer. Here, the authors develop a recommender system ranking genes based on trade-offs between diverse types of evidence linking them to potential mechanisms of EGFRi resistance.

RadSigBench: a framework for benchmarking functional genomics signatures of cancer cell radiosensitivity

Multiple transcriptomic predictors of tumour cell radiosensitivity (RS) have been proposed, but they have not been benchmarked against one another or to control models. To address this, we present RadSigBench, a comprehensive benchmarking framework for RS signatures. The approach compares candidate models to those developed from randomly resampled control signatures and from cellular processes integral to the radiation response. Robust evaluation of signature accuracy, both overall and for individual tissues, is performed. The NCI60 and Cancer Cell Line Encyclopaedia datasets are integrated into our workflow. Prediction of two measures of RS is assessed: survival fraction after 2 Gy and mean inactivation dose. We apply the RadSigBench framework to seven prominent published signatures of radiation sensitivity and test for equivalence to control signatures. The mean out-of-sample R² for the published models on test data was very poor at 0.01 (range: −0.05 to 0.09) for Cancer Cell Line Encyclopedia and 0.00 (range: −0.19 to 0.19) in the NCI60 data. The accuracy of both published and cellular process signatures investigated was equivalent to the resampled controls, suggesting that these signatures contain limited radiation-specific information. Enhanced modelling strategies are needed for effective prediction of intrinsic RS to inform clinical treatment regimes. We make recommendations for methodological improvements, for example the inclusion of perturbation data, multiomics, advanced machine learning and mechanistic modelling. Our validation framework provides for robust performance assessment of ongoing developments in intrinsic RS prediction.

Heterogeneity of Circulating Tumor Cell-Associated Genomic Gains in Breast Cancer and Its Association with the Host Immune Response

Tumor cells that preferentially enter circulation include the precursors of metastatic cancer. Previously, we characterized circulating tumor cells (CTC) from patients with breast cancer and identified a signature of genomic regions with recurrent copy-number gains. Through FISH, we now show that these CTC-associated regions are detected within the matched untreated primary tumors of these patients (21% to 69%, median 55.5%, n = 19). Furthermore, they are more prevalent in the metastases of patients who died from breast cancer after multiple rounds of treatment (70% to 100%, median 93%, samples n = 41). Diversity indices revealed that higher spatial heterogeneity for these regions within primary tumors is associated with increased dissemination and metastasis. An identified subclone with multiple regions gained (MRG clone) was enriched in a posttreatment primary breast carcinoma as well as multiple metastatic tumors and local breast recurrences obtained at autopsy, indicative of a distinct early subclone with the capability to resist multiple lines of treatment and eventually cause death. In addition, multiplex immunofluorescence revealed that tumor heterogeneity is significantly associated with the degree of infiltration of B lymphocytes in triple-negative breast cancer, a subtype with a large immune component. Collectively, these data reveal the functional potential of genetic subclones that comprise heterogeneous primary breast carcinomas and are selected for in CTCs and posttreatment breast cancer metastases. In addition, they uncover a relationship between tumor heterogeneity and host immune response in the tumor microenvironment. SIGNIFICANCE: As breast cancers progress, they become more heterogeneous for multiple regions amplified in circulating tumor cells, and intratumoral spatial heterogeneity is associated with the immune landscape.

Effects from physical exercise on reduced cancer-related fatigue: a systematic review of systematic reviews and meta-analysis

BACKGROUND

Cancer-related fatigue is one of the most prevalent and distressing symptoms among cancer patients, resulting in a great cancer research challenge. Numerous systematic reviews of physical training interventions have been conducted to find the most effective approach. However, evidence remains fragmented, and in which cancer population physical training is more effective than other populations is still unclear. Thus, this study critically appraised systematic reviews and meta-analyses on physical training to reduce adults' cancer-related fatigue.

METHODS

A systematic review of systematic reviews and meta-analysis (PROSPERO: CRD42020189049), assessing the efficacy of exercise training for reducing cancer-related fatigue in adults, was conducted in PubMed, CINAHL, Cochrane Database of Systematic Reviews, and the Database of Abstracts of Reviews of Effects, and Pedro. The selected studies (standardized mean difference, SMD; 95%CI), was quantitatively pooled using a random-effects model. Heterogeneity was tested using chi-squared (Q) and I-square statistics (I²).

RESULTS

Of 1438 identified articles, 11 met the inclusion criteria, and ten were meta-analyzed. The results yielded a positive effect of physical training on fatigue in all cancer populations, SMD = -0.33 (-0.43, -0.23). Subgroup analysis based on tumor localization showed a slightly higher physical training effect on fatigue in adults with breast cancer, SMD = -0.36 (-0.57, -0.15), and prostate cancer SMD = -0.34 (-0.45, -.0.22).

CONCLUSIONS

Our analysis demonstrated some potential improvement in cancer-related fatigue in adult patients undergoing physical training during and after cancer treatments, particularly in patients with breast or prostate cancer.

Tumors Are Evolutionary Island-Like Ecosystems

Integration of ecological and evolutionary features has begun to understand the interplay of tumor heterogeneity, microenvironment, and metastatic potential. Developing a theoretical framework is intrinsic to deciphering tumors' tremendous spatial and longitudinal genetic variation patterns in patients. Here, we propose that tumors can be considered evolutionary island-like ecosystems, that is, isolated systems that undergo evolutionary and spatiotemporal dynamic processes that shape tumor microenvironments and drive the migration of cancer cells. We examine attributes of insular systems and causes of insularity, such as physical distance and connectivity. These properties modulate migration rates of cancer cells through processes causing spatial and temporal isolation of the organs and tissues functioning as a supply of cancer cells for new colonizations. We discuss hypotheses, predictions, and limitations of tumors as islands analogy. We present emerging evidence of tumor insularity in different cancer types and discuss their relevance to the islands model. We suggest that the engagement of tumor insularity into conceptual and mathematical models holds promise to illuminate cancer evolution, tumor heterogeneity, and metastatic potential of cells.

Natural compounds in the regulation of proteostatic pathways: An invincible artillery against stress, ageing, and diseases

Cells have different sets of molecules for performing an array of physiological functions. Nucleic acids have stored and carried the information throughout evolution, whereas proteins have been attributed to performing most of the cellular functions. To perform these functions, proteins need to have a unique conformation and a definite lifespan. These attributes are achieved by a highly coordinated protein quality control (PQC) system comprising chaperones to fold the proteins in a proper three-dimensional structure, ubiquitin-proteasome system for selective degradation of proteins, and autophagy for bulk clearance of cell debris. Many kinds of stresses and perturbations may lead to the weakening of these protective cellular machinery, leading to the unfolding and aggregation of cellular proteins and the occurrence of numerous pathological conditions. However, modulating the expression and functional efficiency of molecular chaperones, E3 ubiquitin ligases, and autophagic proteins may diminish cellular proteotoxic load and mitigate various pathological effects. Natural medicine and small molecule-based therapies have been well-documented for their effectiveness in modulating these pathways and reestablishing the lost proteostasis inside the cells to combat disease conditions. The present article summarizes various similar reports and highlights the importance of the molecules obtained from natural sources in disease therapeutics.

Cancer: An unknown territory; rethinking before going ahead

Cancer is a disease of altered signaling and metabolism, causing uncontrolled division and survival of transformed cells. A host of molecules, factors, and conditions have been designated as underlying causes for the inception and progression of the disease. An enormous amount of data is available, system-wide interaction networks of the genes and proteins are generated over the years and have now reached up to a level of saturation, where we need to shift our focus to the more advanced and comprehensive methods and approaches of data analysis and visualization. Even with the availability of enormous literature on this one of the most pressing pathological conditions, a successful cure of the disease seems to be obscure. New treatment plans, like immunotherapy and precision medicine, are being employed for different studies. Nevertheless, their actual benefits to the patients would be known only after the evaluation of clinical data over the next few years. Therefore, we need to look at few fundamental challenges that should be addressed in more depth before we could devise better, rigorous, and comprehensive treatment plans and may successfully reach a possible cure of the disease. This article aims at bringing attention towards some fundamental gaps in our approach towards the disease that leads to failure in devising successful therapeutics.

Aberrant Promoter Hypermethylation of p16 and RASSF1a Genes in Colorectal Cancer - Significance in Young Patients

OBJECTIVE

The clinical profile of colorectal cancers (CRC) in India is different from that described in western countries. Microsatellite instability and APC mutation explain the molecular biology of up to 50% of colorectal cancers. Global genome hypermethylation may be the cause in at least 20% of cases. Few studies from India have examined the epigenetic profile of colorectal cancers. This study was designed to study aberrant promoter hypermethylation of two select tumour suppressor genes (p16, RASSF1a) in patients with colorectal cancer and their association with clinicopathologic features.

METHODS

A total of 41 samples including controls were collected from colorectal cancer patients. DNA was isolated from tumour tissue, and methylation-specific PCR was performed for the 2 genes.

RESULTS

p16 and RASSF1a promoter hypermethylation was found in 26% and 48% of CRC cases, respectively. RASSF1a promoter hypermethylation was more often seen in young CRC patients aged 40 years or less, and this was found to be statistically significant (p value = 0.037).

CONCLUSION

RASSF1a hypermethylation is peculiar to rectal cancers and left-sided colonic tumours in young patients. Large-scale population-based studies with extensive genetic and epigenetic characterization are required for a better understanding and further validation of our findings. For individuals diagnosed with sporadic CRC, these studies on specimen might help predict prognosis and response to therapy.

EpiPanGI Dx: A Cell-free DNA Methylation Fingerprint for the Early Detection of Gastrointestinal Cancers

PURPOSE

DNA methylation alterations have emerged as front-runners in cell-free DNA (cfDNA) biomarker development. However, much effort to date has focused on single cancers. In this context, gastrointestinal (GI) cancers constitute the second leading cause of cancer-related deaths worldwide; yet there is no blood-based assay for the early detection and population screening of GI cancers.

EXPERIMENTAL DESIGN

Herein, we performed a genome-wide DNA methylation analysis of multiple GI cancers to develop a pan-GI diagnostic assay. By analyzing DNA methylation data from 1,781 tumor and adjacent normal tissues, we first identified differentially methylated regions (DMR) between individual GI cancers and adjacent normal, as well as across GI cancers. We next prioritized a list of 67,832 tissue DMRs by incorporating all significant DMRs across various GI cancers to design a custom, targeted bisulfite sequencing platform. We subsequently validated these tissue-specific DMRs in 300 cfDNA specimens and applied machine learning algorithms to develop three distinct categories of DMR panels RESULTS: We identified three distinct DMR panels: (i) cancer-specific biomarker panels with AUC values of 0.98 (colorectal cancer), 0.98 (hepatocellular carcinoma), 0.94 (esophageal squamous cell carcinoma), 0.90 (gastric cancer), 0.90 (esophageal adenocarcinoma), and 0.85 (pancreatic ductal adenocarcinoma); (ii) a pan-GI panel that detected all GI cancers with an AUC of 0.88; and (iii) a multi-cancer (tissue of origin) prediction panel, EpiPanGI Dx, with a prediction accuracy of 0.85-0.95 for most GI cancers.

CONCLUSIONS

Using a novel biomarker discovery approach, we provide the first evidence for a cfDNA methylation assay that offers robust diagnostic accuracy for GI cancers.

Nanocarriers as a Tool for the Treatment of Colorectal Cancer

Nanotechnology is a promising tool for the treatment of cancer. In the past decades, major steps have been made to bring nanotechnology into the clinic in the form of nanoparticle-based drug delivery systems. The great hope of drug delivery systems is to reduce the side effects of chemotherapeutics while simultaneously increasing the efficiency of the therapy. An increased treatment efficiency would greatly benefit the quality of life as well as the life expectancy of cancer patients. However, besides its many advantages, nanomedicines have to face several challenges and hurdles before they can be used for the effective treatment of tumors. Here, we give an overview of the hallmarks of cancer, especially colorectal cancer, and discuss biological barriers as well as how drug delivery systems can be utilized for the effective treatment of tumors and metastases.

A combination of intra-tumor genetic heterogeneity, estrogen receptor alpha and human papillomavirus status predicts outcomes in head and neck squamous cell carcinoma following chemoradiotherapy

BACKGROUND

Previous work indicates that mutant-allele tumor heterogeneity (MATH), estrogen receptor alpha (ERα) expression, and human papillomavirus (HPV) status provide prognostic utility in head and neck squamous cell carcinoma (HNSCC). We sought to assess whether the combination of these three objective biomarkers could provide better prognostication for patients who receive chemoradiotherapy (CRT).

METHODS

156 patients (75 oral cavity, 44 oropharyngeal and 37 laryngeal squamous cell carcinoma cancer patients) who received CRT as primary therapy or adjuvant to surgery were identified from The Cancer Genome Atlas (TCGA). MATH values were calculated from TCGA whole exome sequencing data, HPV status was determined by mapping RNA-seq reads, and ERα expression was determined from ESR1 mRNA expression data. Relationships among clinical characteristics were assessed by Fisher exact tests. Relationships of clinical characteristics and MATH, ERα and HPV to overall survival were evaluated with Cox proportional hazard analysis.

RESULTS

The combination of poor-prognosis values for all 3 biomarkers (high MATH, low ERα and HPV-negative status) has a predicted hazard ratio of 28.2 (95% CI: 5.4-148, p = 0.0001) versus the combination of their good-prognosis values (low MATH, high ERα and HPV-positive status). Addition of N classification to the combination of these three biomarkers added further prognostic value.

CONCLUSIONS

A combination of these three biomarkers, readily determined on pretreatment biopsy specimens, can stratify patients into prognostic groups. Their application potentially offers numerous opportunities to optimize treatment or explore de-intensification strategies in the clinical trial setting.

Genomic heterogeneity and copy number variant burden are associated with poor recurrence-free survival and 11q loss in human papillomavirus-positive squamous cell carcinoma of the oropharynx

BACKGROUND

Human papillomavirus-positive (HPV+) squamous cell carcinoma of the oropharynx (OPSCC) is the most prevalent HPV-associated malignancy in the United States. Favorable treatment outcomes have led to increased interest in treatment de-escalation to reduce treatment morbidity as well as the development of prognostic markers to identify appropriately low-risk patients. Intratumoral genomic heterogeneity and copy number alteration burden have been demonstrated to be predictive of poor outcomes in many other cancers; therefore, we sought to determine whether intratumor heterogeneity and genomic instability are associated with poor outcomes in HPV+ OPSCC.

METHODS

Tumor heterogeneity estimates were made based on targeted exome sequencing of 45 patients with HPV+ OPSCC tumors. Analysis of an additional cohort of HPV+ OPSCC tumors lacking matched normal sequencing allowed copy number analysis of 99 patient tumors.

RESULTS

High intratumorally genomic heterogeneity and high numbers of copy number alterations were strongly associated with worse recurrence-free survival. Tumors with higher heterogeneity and frequent copy number alterations were associated with loss of distal 11q, which encodes key genes related to double-strand break repair, including ATM and MRE11A.

CONCLUSIONS

Both intratumor genomic heterogeneity and high-burden copy number alterations are strongly associated with poor recurrence-free survival in patients with HPV+ OPSCC. The drivers of genomic instability and heterogeneity in these tumors remains to be elucidated. However, 11q loss and defective DNA double-strand break repair have been associated with genomic instability in other solid tumors. Copy number alteration burden and intratumoral heterogeneity represent promising avenues for risk stratification of patients with HPV+OPSCC.

Symptom clusters in cancer patients: An Italian survey to validate and describe unwarranted clinical variation, inequality in access to healthcare, knowledge, and risk of malpractice

Background and aims:

The perceptions of professionals involved in cancer care regarding the importance of their symptoms-specific knowledge, unwarranted clinical variation (UCV), and inequalities in access to healthcare are still underdescribed. This study aims to confirm the construct validity of a previously initially developed questionnaire and describe nurses’ perceptions about the relevance of their knowledge referred to cancer symptoms management, the UCV, the inequalities in access to healthcare, and malpractice risk.

Method:

A cross-sectional pan-national study was conducted using a convenience sample, collecting data through a previously initially validated questionnaire. Construct validity was corroborated through confirmatory factor analysis, and descriptive statistics were employed for summarizing the questionnaire’s scores. The scores between the nurses working in accredited cancer centers and nurses employed in general hospitals were inferentially compared.

Results:

The sample comprised 810 nurses, 480 were nurses working in accredited cancer centers, and 330 were nurses working in general hospitals. The questionnaire showed adequate construct validity and reliability. Nurses perceived the cluster of psychosocial symptoms with a greater risk of UCV and inequalities in access to cancer services than the cluster of physical symptoms.

Discussion and conclusions:

A paradigm shift aimed at integrating psychosocial cancer symptoms in the care paths emerged as pivotal for improving cancer care in Italy.

Imaging Beyond Seeing: Early Prognosis of Cancer Treatment

Assessing cancer response to therapeutic interventions has been realized as an important course to early predict curative efficacy and treatment outcomes due to tumor heterogeneity. Compared to the traditional invasive tissue biopsy method, molecular imaging techniques have fundamentally revolutionized the ability to evaluate cancer response in a spatiotemporal manner. The past few years has witnessed a paradigm shift on the efforts from manufacturing functional molecular imaging probes for seeing a tumor to a vantage stage of interpreting the tumor response during different treatments. This review is to stand by the current development of advanced imaging technologies aiming to predict the treatment response in cancer therapy. Special interest is placed on the systems that are able to provide rapid and noninvasive assessment of pharmacokinetic drug fates (e.g., drug distribution, release, and activation) and tumor microenvironment heterogeneity (e.g., tumor cells, macrophages, dendritic cells (DCs), T cells, and inflammatory cells). The current status, practical significance, and future challenges of the emerging artificial intelligence (AI) technology and machine learning in the applications of medical imaging fields is overviewed. Ultimately, the authors hope that this review is timely to spur research interest in molecular imaging and precision medicine.

Molecularly Targeted Clinical Trials

Glioblastoma remains incurable despite advances in surgery, radiation, and chemotherapy, underscoring the need for new therapies. The genetic heterogenicity, presence of redundant molecular pathways, and the blood-brain barrier have limited the applicability of molecularly targeted agents. The therapeutic benefit seen with a small subset of patients suggests, however, that patient selection is critical. Recent investigations show that molecularly targeted synthetic lethality is a promising complementary approach. The article provides an overview of the challenges of molecularly targeted therapy in adults with glioblastoma, including current trials and future therapeutic directions.

Reovirus and the Host Integrated Stress Response: On the Frontlines of the Battle to Survive

Cells are continually exposed to stressful events, which are overcome by the activation of a number of genetic pathways. The integrated stress response (ISR) is a large component of the overall cellular response to stress, which ultimately functions through the phosphorylation of the alpha subunit of eukaryotic initiation factor-2 (eIF2α) to inhibit the energy-taxing process of translation. This response is instrumental in the inhibition of viral infection and contributes to evolution in viruses. Mammalian orthoreovirus (MRV), an oncolytic virus that has shown promise in over 30 phase I–III clinical trials, has been shown to induce multiple arms within the ISR pathway, but it successfully evades, modulates, or subverts each cellular attempt to inhibit viral translation. MRV has not yet received Food and Drug Administration (FDA) approval for general use in the clinic; therefore, researchers continue to study virus interactions with host cells to identify circumstances where MRV effectiveness in tumor killing can be improved. In this review, we will discuss the ISR, MRV modulation of the ISR, and discuss ways in which MRV interaction with the ISR may increase the effectiveness of cancer therapeutics whose modes of action are altered by the ISR.

Phycocyanin from Arthrospira platensis as Potential Anti-Cancer Drug: Review of In Vitro and In Vivo Studies

The application of cytostatic drugs or natural substances to inhibit cancer growth and progression is an important and evolving subject of cancer research. There has been a surge of interest in marine bioresources, particularly algae, as well as cyanobacteria and their bioactive ingredients. Dried biomass products of Arthrospira and Chlorella have been categorized as “generally recognized as safe” (GRAS) by the US Food and Drug Administration (FDA). Of particular importance is an ingredient of Arthrospira: phycocyanin, a blue-red fluorescent, water-soluble and non-toxic biliprotein pigment. It is reported to be the main active ingredient of Arthrospira and was shown to have therapeutic properties, including anti-oxidant, anti-inflammatory, immune-modulatory and anti-cancer activities. In the present review, in vitro and in vivo data on the effects of phycocyanin on various tumor cells and on cells from healthy tissues are summarized. The existing knowledge of underlying molecular mechanisms, and strategies to improve the efficiency of potential phycocyanin-based anti-cancer therapies are discussed.

Intratumor heterogeneity could inform the use and type of postoperative adjuvant therapy in patients with head and neck squamous cell carcinoma

BACKGROUND

After surgery for head and neck squamous cell carcinoma (HNSCC), decisions regarding adjuvant radiotherapy (RT) or chemoradiotherapy (CRT) are based on staging and the presence of high-risk pathology. Because higher mutant allele tumor heterogeneity (MATH; a measure of intratumor genetic heterogeneity) is associated with shorter overall survival (OS) in patients with HNSCC, the authors sought to determine whether MATH analysis might further inform these decisions.

METHODS

Adjuvant therapy-associated relationships between MATH and OS were analyzed for 389 patients with HNSCC who were treated surgically. Data were obtained from The Cancer Genome Atlas and analyzed with Cox proportional hazards multiple regression accounting for 7 other patient characteristics.

RESULTS

The relationship between MATH and OS differed with adjuvant therapy in a way that could inform therapy decisions. Adjuvant RT alone was found to provide substantial benefit for patients having high-MATH tumors (RT vs no adjuvant therapy: hazard ratio, 0.29 [95% CI, 0.17-0.51]) but no benefit for those having low-MATH tumors. In contrast, adjuvant CRT provided no benefit beyond that of adjuvant RT for patients with high-MATH tumors but substantially improved OS among patients with low-MATH tumors (CRT vs no adjuvant therapy: hazard ratio, 0.34 [95% CI, 0.15-0.78]).

CONCLUSIONS

The results of the current analysis suggested that patients with HNSCC with high-MATH tumors who underwent surgical treatment could benefit from adjuvant RT, even when current clinical guidelines indicate otherwise. The addition of adjuvant chemotherapy for patients with high-MATH tumors would not be indicated. Adding chemotherapy might be necessary to radiosensitize low-MATH tumors to adjuvant RT. This potential predictive role of tumor MATH analysis should be evaluated in prospective clinical trials.

Epigenetic polypharmacology: A new frontier for epi-drug discovery

Recently, despite the great success achieved by the so-called "magic bullets" in the treatment of different diseases through a marked and specific interaction with the target of interest, the pharmacological research is moving toward the development of "molecular network active compounds," embracing the related polypharmacology approach. This strategy was born to overcome the main limitations of the single target therapy leading to a superior therapeutic effect, a decrease of adverse reactions, and a reduction of potential mechanism(s) of drug resistance caused by robustness and redundancy of biological pathways. It has become clear that multifactorial diseases such as cancer, neurological, and inflammatory disorders, may require more complex therapeutic approaches hitting a certain biological system as a whole. Concerning epigenetics, the goal of the multi-epi-target approach consists in the development of small molecules able to simultaneously and (often) reversibly bind different specific epi-targets. To date, two dual histone deacetylase/kinase inhibitors (CUDC-101 and CUDC-907) are in an advanced stage of clinical trials. In the last years, the growing interest in polypharmacology encouraged the publication of high-quality reviews on combination therapy and hybrid molecules. Hence, to update the state-of-the-art of these therapeutic approaches avoiding redundancy, herein we focused only on multiple medication therapies and multitargeting compounds exploiting epigenetic plus nonepigenetic drugs reported in the literature in 2018. In addition, all the multi-epi-target inhibitors known in literature so far, hitting two or more epigenetic targets, have been included.

Zebrafish Models of Cancer-New Insights on Modeling Human Cancer in a Non-Mammalian Vertebrate

Zebrafish (Danio rerio) is a valuable non-mammalian vertebrate model widely used to study development and disease, including more recently cancer. The evolutionary conservation of cancer-related programs between human and zebrafish is striking and allows extrapolation of research outcomes obtained in fish back to humans. Zebrafish has gained attention as a robust model for cancer research mainly because of its high fecundity, cost-effective maintenance, dynamic visualization of tumor growth in vivo, and the possibility of chemical screening in large numbers of animals at reasonable costs. Novel approaches in modeling tumor growth, such as using transgene electroporation in adult zebrafish, could improve our knowledge about the spatial and temporal control of cancer formation and progression in vivo. Looking at genetic as well as epigenetic alterations could be important to explain the pathogenesis of a disease as complex as cancer. In this review, we highlight classic genetic and transplantation models of cancer in zebrafish as well as provide new insights on advances in cancer modeling. Recent progress in zebrafish xenotransplantation studies and drug screening has shown that zebrafish is a reliable model to study human cancer and could be suitable for evaluating patient-derived xenograft cell invasiveness. Rapid, large-scale evaluation of in vivo drug responses and kinetics in zebrafish could undoubtedly lead to new applications in personalized medicine and combination therapy. For all of the above-mentioned reasons, zebrafish is approaching a future of being a pre-clinical cancer model, alongside the mouse. However, the mouse will continue to be valuable in the last steps of pre-clinical drug screening, mostly because of the highly conserved mammalian genome and biological processes.

Gene silencing by double-stranded RNA from C. elegans neurons reveals functional mosaicism of RNA interference

Delivery of double-stranded RNA (dsRNA) into animals can silence genes of matching sequence in diverse cell types through mechanisms that have been collectively called RNA interference. In the nematode Caenorhabditis elegans, dsRNA from multiple sources can trigger the amplification of silencing signals. Amplification occurs through the production of small RNAs by two RNA-dependent RNA polymerases (RdRPs) that are thought to be tissue-specific - EGO-1 in the germline and RRF-1 in somatic cells. Here we demonstrate that EGO-1 can compensate for the lack of RRF-1 when dsRNA from neurons is used to silence genes in intestinal cells. However, the lineal origins of cells that can use EGO-1 varies. This variability could be because random sets of cells can either receive different amounts of dsRNA from the same source or use different RdRPs to perform the same function. Variability is masked in wild-type animals, which show extensive silencing by neuronal dsRNA. As a result, cells appear similarly functional despite underlying differences that vary from animal to animal. This functional mosaicism cautions against inferring uniformity of mechanism based on uniformity of outcome. We speculate that functional mosaicism could contribute to escape from targeted therapies and could allow developmental systems to drift over evolutionary time.

HIF-1α rs11549465 C>T polymorphism contributes to increased cancer susceptibility: Evidence from 49 studies

HIF-1α (hypoxia-inducible factor-1α) is a transcriptional factor that participates in the regulation of oxygen homeostasis. Despites numbers of case-control studies working on this area, the actual relationship of HIF-1α gene generic variant rs11549465 C>T imposing on cancer susceptibility remains unveiled. To get a better understanding of such relationship, this meta-analysis was carried out by incorporating all eligible case-control studies. Qualified articles were acquired from PubMed, CNKI, EMBASE, PMC, and Wanfang database update to April 2019. Odds ratios (ORs) and their corresponding 95% confidence intervals (CIs) were employed to estimate the relationship of interest. Heterogeneity tests, sensitivity analyses and publication bias assessments were also carried out to ensure the strength of our conclusion. A total of 46 articles with 49 studies including 12920 cases and 13363 controls were included. The results indicated that HIF-1α rs11549465 C>T was significantly related to the increased risk of overall cancer under four genetic models (TT vs. CC: OR=2.06, 95% CI=1.34-3.16; TT vs. CC/CT: OR=2.42, 95% CI=1.60-3.65; CT/TT vs. CC: OR=1.21, 95% CI=1.04-1.40; T vs. C: OR=1.29, 95% CI=1.12-1.48). Furthermore, enhanced cancer risk was detected after stratification by cancer type, ethnicity, the source of controls and HWE. These results suggest that HIF-1α rs11549465 C>T polymorphism may predispose to cancer susceptibility.

Genomics-Guided Immunotherapy for Precision Medicine in Cancer

Next-generation sequencing (NGS) data have been central to the development of targeted therapy and immunotherapy for precision oncology. In targeted therapy, drugs directly attack cancer, by altering the expression of critical cancer genes identified with cancer genome profiling. Immunotherapy drugs indirectly attack cancer, by inducing the immune system to attack and treat cancer. Harnessing genomic data for deployment and development of immunotherapy comprises the field of immunogenomics. The discovery of a link between cancer cells escaping immune destruction and cancer progression, led to extensive research into this mechanism and drug development. In the past few years, FDA has granted accelerated approval to several immunotherapy cancer treatment drugs, pembrolizumab, nivolumab, and atezolizumab, belonging to the class of checkpoint inhibitors. Utilization of pretreatment genomic cancer screening to identify patients most likely to respond to immunotherapy and to customize immunotherapy for a given patient, promises to improve cancer treatment outcomes. Recent advances in molecular profiling, high-throughput sequencing, and computational efficiency has made immunogenomics the major tenet of precision medicine in cancer treatment. This review provides a brief overview on the state of art of immunogenomics in precision cancer medicine.

The immune system profoundly restricts intratumor genetic heterogeneity

Tumors develop under the selective pressure of the immune system. However, it remains critical to establish how the immune system affects the clonal heterogeneity of tumors that often display cell-to-cell variation in genetic alterations and antigenic expression. To address these questions, we introduced a multicolor barcoding strategy to study the growth of a MYC-driven B cell lymphoma harboring a large degree of intratumor genetic diversity. Using intravital imaging, we visualized that lymphoma subclones grow as patches of sessile cells in the bone marrow, creating a spatially compartmentalized architecture for tumor diversity. Using multicolor barcoding and whole-exome sequencing, we demonstrated that immune responses strongly restrict intratumor genomic diversity and favor clonal dominance, a process mediated by the selective elimination of more immunogenic cells and amplified by epitope spreading. Anti-PD-1 treatment also narrowed intratumor diversity. Our results provide direct evidence that immune pressure shapes the level of intratumor genetic heterogeneity and have important implications for the design of therapeutic strategies.

A meta-analysis of multiple matched aCGH/expression cancer datasets reveals regulatory relationships and pathway enrichment of potential oncogenes

The copy numbers of genes in cancer samples are often highly disrupted and form a natural amplification/deletion experiment encompassing multiple genes. Matched array comparative genomics and transcriptomics datasets from such samples can be used to predict inter-chromosomal gene regulatory relationships. Previously we published the database METAMATCHED, comprising the results from such an analysis of a large number of publically available cancer datasets. Here we investigate genes in the database which are unusual in that their copy number exhibits consistent heterogeneous disruption in a high proportion of the cancer datasets. We assess the potential relevance of these genes to the pathology of the cancer samples, in light of their predicted regulatory relationships and enriched biological pathways. A network-based method was used to identify enriched pathways from the genes’ inferred targets. The analysis predicts both known and new regulator-target interactions and pathway memberships. We examine examples in detail, in particular the gene POGZ, which is disrupted in many of the cancer datasets and has an unusually large number of predicted targets, from which the network analysis predicts membership of cancer related pathways. The results suggest close involvement in known cancer pathways of genes exhibiting consistent heterogeneous copy number disruption. Further experimental work would clarify their relevance to tumor biology. The results of the analysis presented in the database METAMATCHED, and included here as an R archive file, constitute a large number of predicted regulatory relationships and pathway memberships which we anticipate will be useful in informing such experiments.

A novel knowledge-derived data potentizing method revealed unique liver cancer-associated genetic variants

Background

Next-generation sequencing (NGS) has been advancing the progress of detection of disease-associated genetic variants and genome-wide profiling of expressed sequences over the past decade. NGS enables the analyses of multiple regions of a genome in a single reaction format and has been shown to be a cost-effective and efficient tool for root-cause analysis of disease and optimization of treatment. NGS has been leading global efforts to device personalized and precision medicine (PM) in clinical practice. The effectiveness of NGS for the aforementioned applications has been proven unequivocal for multifactorial diseases like cancer. However, definitive prediction of cancer markers for all types of diseases and for global populations still remains highly rewarding because of the diversity of cancer types and genetic variants in human.

Results

We performed exome sequencing of four samples in quest of critical genetic factor/s associated with liver cancer. By imposing knowledge-based filter chains, we have revealed a panel of genetic variants, which are unrecognized by current major genomics data repositories. Total 20 MNV-induced, 5 INDEL-induced, and 31 SNV-induced neoplasm-exclusive genes were revealed through NGS data acquisition followed by data curing with the application of quality filter chains. Liver-specific expression profile of the identified gene pool is directed to the selection of 17 genes which could be the as likely causative genetic factors for liver cancer. Further study on expression level and relevant functional significance enables us to identify and conclude the following four novel variants, viz., c.416T>C (p.Phe139Ser) in SORD, c.1048_1049delGCinsCG (p.Ala350Arg) in KRT6A, c.1159G>T (p.Gly387Cys) in SVEP1, and c.430G>C (p.Gly144Arg) in MRPL38 as a critical genetic factor for liver cancer.

Conclusion

By applying a novel data prioritizing rationale, we explored a panel of previously unaddressed liver cancer-associated variants. These findings may have an opportunity for early prediction of neoplasm/cancer in liver and designing of relevant personalized/precision liver cancer therapeutics in clinical practice. Since NGS protocol is associated with tons of non-specific mutations due to the variation in background genetic makeup of subjects, therefore, our method of data curing could be applicable for more effective screening of global genetic variants related to disease onset, progression, and remission.

Electronic supplementary material

The online version of this article (10.1186/s40246-019-0213-7) contains supplementary material, which is available to authorized users.

Micellar Formulation of Talazoparib and Buparlisib for Enhanced DNA Damage in Breast Cancer Chemoradiotherapy

Chemoradiation is an effective combined modality therapeutic approach that utilizes principles of spatial cooperation to combat the adaptability associated with cancer and to potentially expand the therapeutic window. Optimal therapeutic efficacy requires intelligent selection and refinement of radiosynergistic pharmaceutical agents, enhanced delivery methods, and temporal consideration. Here, a monodisperse sub-20 nm mixed poloxamer micelle (MPM) system was developed to deliver hydrophobic drugs intravenously, in tandem with ionizing radiation. This report demonstrates in vitro synergy and enhanced radiosensitivity when two molecularly targeted DNA repair inhibitors, talazoparib and buparlisib, are encapsulated and combined with radiation in a 4T1 murine breast cancer model. Evaluation of in vivo biodistribution and toxicity exhibited no reduction in particle accumulation upon radiation and a lack of both acute and chronic toxicities. In vivo efficacy studies suggested the promise of combining talazoparib, buparlisib, and radiation to enhance survival and control tumor growth. Tissue analysis suggests enhanced DNA damage leading to apoptosis, thus increasing efficacy. These findings highlight the challenges associated with utilizing clinically relevant inclusion criteria and treatment protocols because complete tumor regression and extended survival were masked by an aggressively metastasizing model. As with clinical treatment regimens, the findings here establish a need for further optimization of this multimodal platform.

Methylation of the claudin‑3 promoter predicts the prognosis of advanced gastric adenocarcinoma

Claudin-3 expression is associated with gastric cancer progression, but the role of epigenetic modifications remains unclear. We investigated methylation of the claudin-3 promoter and expression profiles in gastric adenocarcinoma and their associations with clinicopathological characteristics and prognosis of the patients. A total of 122 patients with advanced gastric cancer [stage IIB-IV, with lymph node (LN) metastasis] were enrolled. Each patient provided 4 tissue samples: normal gastric epithelium, intestinal metaplasia, primary tumor and metastatic LN. Claudin-3 protein expression was examined by immunohistochemistry. Claudin-3 promoter methylation was determined by methylation-specific PCR and verified by bisulfite sequencing PCR. Claudin-3 mRNA expression was measured by real-time PCR in a subset of cases, and its correlation with protein expression was analyzed using Spearman correlation. Kaplan-Meier survival analysis was performed (log-rank test). Factors associated with survival were identified by Cox regression. The strong expression rate of claudin-3 in intestinal metaplasia, primary tumor, metastatic LN and normal gastric epithelium was 91.8, 58.2, 30.3 and 13.9%, respectively. The promoter hypermethylation rate in intestinal metaplasia, primary tumor, normal gastric epithelium and metastatic LN was 5.7, 27.9, 36.9 and 49.2%, respectively. Claudin-3 mRNA and protein expression were positively correlated (P<0.001) with normal gastric epithelium (r_s=0.745), intestinal metaplasia (r_s=0.876), primary gastric adenocarcinoma (r_s=0.915) and metastatic LN (r_s=0.819). Claudin-3 mRNA expression was negatively correlated with claudin-3 promoter methylation. Median patient survival was 38, 22 and 11 months in the hypomethylated, partially methylated and hypermethylated groups, respectively (P<0.001). Claudin-3 promoter methylation status (HR: 5.67; 95% CI: 2.27–14.17) but not claudin-3 expression was an independent predictor of survival. Claudin-3 promoter hypermethylation reduces claudin-3 expression and independently predicts poor prognosis.

Somatic evolutionary timings of driver mutations

BACKGROUND

A unified analysis of DNA sequences from hundreds of tumors concluded that the driver mutations primarily occur in the earliest stages of cancer formation, with relatively few driver mutation events detected in the late-arising subclones. However, emerging evidence from the sequencing of multiple tumors and tumor regions per individual suggests that late-arising subclones with additional driver mutations are underestimated in single-sample analyses.

METHODS

To test whether driver mutations generally map to early tumor development, we examined multi-regional tumor sequencing data from 101 individuals reported in 11 published studies. Following previous studies, we annotated mutations as early-arising when all tumors/regions had those mutations (ubiquitous). We then inferred the fraction of mutations occurring early and compared it with late-arising mutations that were found in only single tumors/regions.

RESULTS

While a large fraction of driver mutations in tumors occurred relatively early in cancers, later driver mutations occurred at least as frequently as the early drivers in a substantial number of patients. This result was robust to many different approaches to annotate driver mutations. The relative frequency of early and late driver mutations varied among patients of the same cancer type and in different cancer types. We found that previous reports of the preponderance of early driver mutations were primarily informed by analysis of single tumor variant allele profiles, with which it is challenging to clearly distinguish between early and late drivers.

CONCLUSIONS

The origin and preponderance of new driver mutations are not limited to early stages of tumor evolution, with different tumors and regions showing distinct driver mutations and, consequently, distinct characteristics. Therefore, tumors with extensive intratumor heterogeneity appear to have many newly acquired drivers.