The Role of Tumor Microenvironment in Genomic Instability of Malignant Tumors

The Warburg hypothesis and the emergence of the mitochondrial metabolic theory of cancer

Otto Warburg originally proposed that cancer arose from a two-step process. The first step involved a chronic insufficiency of mitochondrial oxidative phosphorylation (OxPhos), while the second step involved a protracted compensatory energy synthesis through lactic acid fermentation. His extensive findings showed that oxygen consumption was lower while lactate production was higher in cancerous tissues than in non-cancerous tissues. Warburg considered both oxygen consumption and extracellular lactate as accurate markers for ATP production through OxPhos and glycolysis, respectively. Warburg's hypothesis was challenged from findings showing that oxygen consumption remained high in some cancer cells despite the elevated production of lactate suggesting that OxPhos was largely unimpaired. New information indicates that neither oxygen consumption nor lactate production are accurate surrogates for quantification of ATP production in cancer cells. Warburg also did not know that a significant amount of ATP could come from glutamine-driven mitochondrial substrate level phosphorylation in the glutaminolysis pathway with succinate produced as end product, thus confounding the linkage of oxygen consumption to the origin of ATP production within mitochondria. Moreover, new information shows that cytoplasmic lipid droplets and elevated aerobic lactic acid fermentation are both biomarkers for OxPhos insufficiency. Warburg's original hypothesis can now be linked to a more complete understanding of how OxPhos insufficiency underlies dysregulated cancer cell growth. These findings can also address several questionable assumptions regarding the origin of cancer thus allowing the field to advance with more effective therapeutic strategies for a less toxic metabolic management and prevention of cancer.

The Hallmarks of Cancer as Eco-Evolutionary Processes

SIGNIFICANCE

Viewing the hallmarks as a sequence of adaptations captures the "why" behind the "how" of the molecular changes driving cancer. This eco-evolutionary view distils the complexity of cancer progression into logical steps, providing a framework for understanding all existing and emerging hallmarks of cancer and developing therapeutic interventions.

Genomic Landscape of Breast Cancer: Study Across Diverse Ethnic Groups

Background: Breast cancer (BC) is the most common cancer among women worldwide, with incidence and mortality rates varying across ethnic groups due to sociodemographic, clinicopathological, and genomic differences. This study aimed to characterize the genomic landscape of BC in diverse ethnic groups using computational tools to explore these variations. Methodology: cBioPortal was used to analyze genomic, clinicopathological, and sociodemographic data from 1084 BC samples. Mutated genes were classified based on GeneCards platform data. Enrichment analysis was performed with CancerHallmarks, and genes not found were compared with MSigDB's Hallmark Gene Sets. Genes absent from both were further analyzed using NDEx through Cytoscape.org to explore their role in cancer. Results: Significant differences (p < 0.05) were observed in sex, tumor subtypes, genetic ancestry, median of the fraction of the altered genome, mutation count, and mutation frequencies of genes across ethnic groups. We identified the most frequently mutated genes. Some of these genes were found to be associated with classic cancer hallmarks, such as replicative immortality, sustained proliferative signaling, and the evasion of growth suppressors. However, the exact role of some of these genes in cancer remains unclear, highlighting the need for further research to better understand their involvement in tumor biology. Conclusions: This study identified significant clinicopathological and genomic variations in BC across ethnic groups. While key genes associated with cancer hallmarks were found, the incomplete characterization of some highlights the need for further research, especially focusing on ethnic groups, to understand their role in tumor biology and improve personalized treatments.

Identification of Genomic Instability-Associated LncRNAs as Potential Therapeutic Targets in Lung Adenocarcinoma

BACKGROUND/OBJECTIVES

Non-small cell lung cancer (NSCLC) is the most common type of cancer, with lung adenocarcinoma (LUAD) as the predominant subtype. Despite advancements in targeted therapies, many NSCLC patients still experience poor outcomes due to treatment resistance and disease progression. Genomic instability (GI), a hallmark of cancer, defined as the increased tendency of DNA mutations and alterations, is closely linked to cancer initiation, progression, and resistance to therapy. Emerging evidence suggests that long non-coding RNAs (lncRNAs)-molecules longer than 200 nucleotides that do not encode proteins but regulate gene expression-play critical roles in cancer biology and are associated with GI. However, the relationship between GI and lncRNA expression in LUAD remains poorly understood.

METHODS

In this study, we analyzed the transcript profiles of lncRNAs and mRNAs from LUAD samples in The Cancer Genome Atlas (TCGA) database and classified them based on their Homologous Recombination Deficiency (HRD) score. The HRD score is an unweighted sum of three independent DNA-based measures of genomic instability: loss of heterozygosity, telomeric allelic imbalance, and large-scale transitions. We then performed a differential gene expression analysis to identify lncRNAs and mRNAs that were either upregulated or downregulated in samples with high HRD scores compared to those with low HRD scores. Following this, we conducted a correlation analysis to assess the significance of the association between HRD scores and the expression of both lncRNAs and mRNAs.

RESULTS

We identified 30 differentially expressed lncRNAs and 200 mRNAs associated with genomic instability. Using an RNA interactome database from sequencing experiments, we found evidence of interactions between GI-associated lncRNAs (GI-lncRNAs) and GI-associated mRNAs (GI-mRNAs). Further investigation showed that some GI-lncRNAs play regulatory and functional roles in LUAD and other diseases. We also found that GI-lncRNAs have potential as prognostic biomarkers, particularly when integrated with HRD stratification. The expression of specific GI-lncRNAs was associated with primary therapy response and immune infiltration in LUAD. Additionally, we identified existing drugs that could modulate GI-lncRNAs, offering potential therapeutic strategies to address GI in LUAD.

CONCLUSIONS

Our findings suggest that GI-associated lncRNAs could serve as valuable biomarkers for LUAD prognosis and therapeutic response. Furthermore, modulating these lncRNAs presents potential treatment avenues to address genomic instability in LUAD.

Role of Soluble Cytokine Receptors in Gastric Cancer Development and Chemoresistance

Gastric cancer is among the top five most important malignancies in the world due to the high burden of the disease and its lethality. Indeed, it is the fourth most common cause of death worldwide, characterized by a poor prognosis and low responsiveness to chemotherapy. Multidrug resistance limits the clinical management of the patient. Among these, the role of chronic activation of inflammatory pathways underlying gastric tumorigenesis should be highlighted. Furthermore, the gastric immunosuppressive TME influences the response to therapy. This review discusses the role of soluble cytokine receptors in the development and chemoresistance of gastric cancer, considered as a molecular marker and target of strategies to overcome resistance.

Compressive stresses in cancer: characterization and implications for tumour progression and treatment

Beyond their many well-established biological aberrations, solid tumours create an abnormal physical microenvironment that fuels cancer progression and confers treatment resistance. Mechanical forces impact tumours across a range of biological sizes and timescales, from rapid events at the molecular level involved in their sensing and transmission, to slower and larger-scale events, including clonal selection, epigenetic changes, cell invasion, metastasis and immune response. Owing to challenges with studying these dynamic stimuli in biological systems, the mechanistic understanding of the effects and pathways triggered by abnormally elevated mechanical forces remains elusive, despite clear correlations with cancer pathophysiology, aggressiveness and therapeutic resistance. In this Review, we examine the emerging and diverse roles of physical forces in solid tumours and provide a comprehensive framework for understanding solid stress mechanobiology. We first review the physiological importance of mechanical forces, especially compressive stresses, and discuss their defining characteristics, biological context and relative magnitudes. We then explain how abnormal compressive stresses emerge in tumours and describe the experimental challenges in investigating these mechanically induced processes. Finally, we discuss the clinical translation of mechanotherapeutics that alleviate solid stresses and their potential to synergize with chemotherapy, radiotherapy and immunotherapies.

Claudin-4 Modulates Autophagy via SLC1A5/LAT1 as a Mechanism to Regulate Micronuclei

Genome instability is a hallmark of cancer crucial for tumor heterogeneity and is often a result of defects in cell division and DNA damage repair. Tumors tolerate genomic instability, but the accumulation of genetic aberrations is regulated to avoid catastrophic chromosomal alterations and cell death. In ovarian cancer tumors, claudin-4 is frequently upregulated and closely associated with genome instability and worse patient outcomes. However, its biological association with regulating genomic instability is poorly understood. Here, we used CRISPR interference and a claudin mimic peptide to modulate the claudin-4 expression and its function in vitro and in vivo. We found that claudin-4 promotes a tolerance mechanism for genomic instability through micronuclei generation in tumor cells. Disruption of claudin-4 increased autophagy and was associated with the engulfment of cytoplasm-localized DNA. Mechanistically, we observed that claudin-4 establishes a biological axis with the amino acid transporters SLC1A5 and LAT1, which regulate autophagy upstream of mTOR. Furthermore, the claudin-4/SLC1A5/LAT1 axis was linked to the transport of amino acids across the plasma membrane as one of the potential cellular processes that significantly decreased survival in ovarian cancer patients. Together, our results show that the upregulation of claudin-4 contributes to increasing the threshold of tolerance for genomic instability in ovarian tumor cells by limiting its accumulation through autophagy.

SIGNIFICANCE

Autophagy regulation via claudin-4/SLC1A5/LAT1 has the potential to be a targetable mechanism to interfere with genomic instability in ovarian tumor cells.

Evaluating Leukocyte Telomere Length and Myeloid-Derived Suppressor Cells as Biomarkers for Prostate Cancer

BACKGROUND

Leukocyte telomere length (LTL) and myeloid-derived suppressor cells (MDSC) are associated with aging and the development and progression of cancer. However, the exact nature of this relationship remains unclear. Our study aimed to investigate the potential of LTL and MDSC as diagnostic biomarkers for prostate cancer while also seeking to deepen our understanding of the relationship of these potential biomarkers to each other.

METHODS

Our study involved patients undergoing a prostate biopsy. We analyzed the relative LTL in genomic DNA obtained from peripheral blood leukocytes as well as the percentage of MDSC and their subtypes in peripheral blood mononuclear cells (PBMC). Our evaluation focused on examining the relationship between LTL and MDSC and pathological diagnoses as well as investigating the correlation between LTL and MDSC levels.

RESULTS

In our study of 102 participants, 56 were pathologically diagnosed with localized prostate cancer (cancer group), while 46 tested negative (control group). The cancer group exhibited significantly shorter LTL in comparison to the control group (p = 0.024). Additionally, the cancer group showed a tendency towards a higher percentage of monocytic MDSC (M-MDSC), although this difference did not reach statistical significance (p = 0.056). Our multivariate logistic regression analysis revealed that patients with shorter LTL and higher percentages of M-MDSC had a 2.98-fold (95% CI = 1.001-8.869, p = 0.049) and 3.03-fold (95% CI = 1.152-7.977, p = 0.025) increased risk of prostate cancer diagnosis, respectively. There was also a significant negative correlation between LTL and M-MDSC. (r = -0.347, p < 0.001).

CONCLUSIONS

Our research has established a correlation between LTL and MDSC in patients undergoing biopsy for prostate cancer. Notably, we observed that individuals with localized prostate cancer tend to have shorter LTL and a higher percentage of M-MDSC prior to their diagnosis. These findings suggest that LTL and M-MDSC could potentially serve as adjunctive biomarkers for the early diagnosis of prostate cancer.

G-quadruplex-mediated genomic instability drives SNVs in cancer

G-quadruplex (G4s) DNA structures have been implicated in inducing genomic instability and contributing to cancer development. However, the relationship between G4s and cancer-related single nucleotide variants (cSNVs) in clinical settings remains unclear. In this large-scale study, we integrated experimentally validated G4s with genomic cSNVs from 13480 cancer patients to investigate the spatial association of G4s with the cellular cSNV landscape. Our findings demonstrate an increase in local genomic instability with increasing local G4 content in cancer patients, suggesting a potential role for G4s in driving cSNVs. Notably, we observed distinct spatial patterns of cSNVs and common single nucleotide variants (dbSNVs) in relation to G4s, implying different mechanisms for their generation and accumulation. We further demonstrate large, cancer-specific differences in the relationship of G4s and cSNVs, which could have important implications for a new class of G4-stabilizing cancer therapeutics. Moreover, we show that high G4-content can serve as a prognostic marker for local cSNV density and patient survival rates. Our findings underscore the importance of considering G4s in cancer research and highlight the need for further investigation into the underlying molecular mechanisms of G4-mediated genomic instability, especially in the context of cancer.

Claudin-4 modulates autophagy via SLC1A5/LAT1 as a tolerance mechanism for genomic instability in ovarian cancer

Genome instability is key for tumor heterogeneity and derives from defects in cell division and DNA damage repair. Tumors show tolerance for this characteristic, but its accumulation is regulated somehow to avoid catastrophic chromosomal alterations and cell death. Claudin-4 is upregulated and closely associated with genome instability and worse patient outcome in ovarian cancer. This protein is commonly described as a junctional protein participating in processes such as cell proliferation and DNA repair. However, its biological association with genomic instability is still poorly-understood. Here, we used CRISPRi and a claudin mimic peptide (CMP) to modulate the cladudin-4 expression and its function, respectively in in-vitro (high-grade serous carcinoma cells) and in-vivo (patient-derived xenograft in a humanized-mice model) systems. We found that claudin-4 promotes a protective cellular-mechanism that links cell-cell junctions to genome integrity. Disruption of this axis leads to irregular cellular connections and cell cycle that results in chromosomal alterations, a phenomenon associated with a novel functional link between claudin-4 and SLC1A5/LAT1 in regulating autophagy. Consequently, claudin-4's disruption increased autophagy and associated with engulfment of cytoplasm-localized DNA. Furthermore, the claudin-4/SLC1A5/LAT1 biological axis correlates with decrease ovarian cancer patient survival and targeting claudin-4 in-vivo with CMP resulted in increased niraparib (PARPi) efficacy, correlating with increased tumoral infiltration of T CD8+ lymphocytes. Our results show that the upregulation of claudin-4 enables a mechanism that promotes tolerance to genomic instability and immune evasion in ovarian cancer; thus, suggesting the potential of claudin-4 as a translational target for enhancing ovarian cancer treatment.

TK1 expression influences pathogenicity by cell cycle progression, cellular migration, and cellular survival in HCC 1806 breast cancer cells

Breast cancer is the most common cancer diagnosis worldwide accounting for 1 out of every 8 cancer diagnoses. The elevated expression of Thymidine Kinase 1 (TK1) is associated with more aggressive tumor grades, including breast cancer. Recent studies indicate that TK1 may be involved in cancer pathogenesis; however, its direct involvement in breast cancer has not been identified. Here, we evaluate potential pathogenic effects of elevated TK1 expression by comparing HCC 1806 to HCC 1806 TK1-knockdown cancer cells (L133). Transcriptomic profiles of HCC 1806 and L133 cells showed cell cycle progression, apoptosis, and invasion as potential pathogenic pathways affected by TK1 expression. Subsequent in-vitro studies confirmed differences between HCC 1806 and L133 cells in cell cycle phase progression, cell survival, and cell migration. Expression comparison of several factors involved in these pathogenic pathways between HCC 1806 and L133 cells identified p21 and AKT3 transcripts were significantly affected by TK1 expression. Creation of a protein-protein interaction map of TK1 and the pathogenic factors we evaluated predict that the majority of factors evaluated either directly or indirectly interact with TK1. Our findings argue that TK1 elevation directly increases HCC 1806 cell pathogenicity and is likely occurring by p21- and AKT3-mediated mechanisms to promote cell cycle arrest, cellular migration, and cellular survival.

Molecular and immunological mechanisms of clonal evolution in multiple myeloma

Multiple myeloma (MM) is a hematologic malignancy characterized by the proliferation of clonal plasma cells in the bone marrow (BM). It is known that early genetic mutations in post-germinal center B/plasma cells are the cause of myelomagenesis. The acquisition of additional chromosomal abnormalities and distinct mutations further promote the outgrowth of malignant plasma cell populations that are resistant to conventional treatments, finally resulting in relapsed and therapy-refractory terminal stages of MM. In addition, myeloma cells are supported by autocrine signaling pathways and the tumor microenvironment (TME), which consists of diverse cell types such as stromal cells, immune cells, and components of the extracellular matrix. The TME provides essential signals and stimuli that induce proliferation and/or prevent apoptosis. In particular, the molecular pathways by which MM cells interact with the TME are crucial for the development of MM. To generate successful therapies and prevent MM recurrence, a thorough understanding of the molecular mechanisms that drive MM progression and therapy resistance is essential. In this review, we summarize key mechanisms that promote myelomagenesis and drive the clonal expansion in the course of MM progression such as autocrine signaling cascades, as well as direct and indirect interactions between the TME and malignant plasma cells. In addition, we highlight drug-resistance mechanisms and emerging therapies that are currently tested in clinical trials to overcome therapy-refractory MM stages.

Delineating intra-tumoral heterogeneity and tumor evolution in breast cancer using precision-based approaches

The burden of breast cancer continues to increase worldwide as it remains the most diagnosed tumor in females and the second leading cause of cancer-related deaths. Breast cancer is a heterogeneous disease characterized by different subtypes which are driven by aberrations in key genes such as BRCA1 and BRCA2, and hormone receptors. However, even within each subtype, heterogeneity that is driven by underlying evolutionary mechanisms is suggested to underlie poor response to therapy, variance in disease progression, recurrence, and relapse. Intratumoral heterogeneity highlights that the evolvability of tumor cells depends on interactions with cells of the tumor microenvironment. The complexity of the tumor microenvironment is being unraveled by recent advances in screening technologies such as high throughput sequencing; however, there remain challenges that impede the practical use of these approaches, considering the underlying biology of the tumor microenvironment and the impact of selective pressures on the evolvability of tumor cells. In this review, we will highlight the advances made thus far in defining the molecular heterogeneity in breast cancer and the implications thereof in diagnosis, the design and application of targeted therapies for improved clinical outcomes. We describe the different precision-based approaches to diagnosis and treatment and their prospects. We further propose that effective cancer diagnosis and treatment are dependent on unpacking the tumor microenvironment and its role in driving intratumoral heterogeneity. Underwriting such heterogeneity are Darwinian concepts of natural selection that we suggest need to be taken into account to ensure evolutionarily informed therapeutic decisions.

Immune infiltration and drug specificity analysis of different subtypes based on functional status in angioimmunoblastic T-cell lymphoma

Angioimmunoblastic T-cell lymphoma (AITL) is a subtype of peripheral T-cell lymphoma (PTCL) strongly correlated with worse clinical outcomes. However, the role of characteristic pathway-related genes in patients with AITL (e.g., subtype typing and pathogenesis) remains unknown. In this study, we intended to understand the potential role and prognostic value of characteristic pathways in AITL and identified a model for subtype identification based on pathway-related functional status. Transcriptomic (RNA-seq) data were obtained from the Gene Expression Omnibus database for three sets of tumor tissues from AITL patients. AITL was divided into three clusters based on the pathway profile of patients and the best clustering k = 3, and differentially expressed genes (DEGs) in the three clusters were analyzed. The top 45 important variables associated with characteristic pathways, such as Huntington's disease, VEGF signaling pathway, nucleotide excision repair, ubiquitin-mediated proteolysis, purine metabolism, olfactory transduction, etc., were used to construct a subtype identification model. The model was experimentally validated and proved to possess good predictive efficacy. In addition, pathway-related subtype typing was significantly associated with different immune cell infiltration in AITL. Further analysis revealed that the drug IC50 values predicted also differed markedly among the different subtypes, thus further identifying some subtype-specific drugs. Our study indicates a potential role of characteristic pathways in AITL staging for the first time, provides novel insights for future research targeting AITL, and points to potential therapeutic options for patients with different subtypes of AITL.

Overexpressed kinetochore genes are used by cancer cells as genome destabilizers and transformation catalysts

Cancer cells have an altered transcriptome, which contributes to their abnormal behavior. Many tumors have high levels of kinetochore genes, which play important roles in genome stability. This overexpression could be utilized to destabilize cancer cell genomes, however this has not been proven specifically. We investigated the link between kinetochore gene overexpression, chromosomal number variations (CNVs) and genomic instability. Data on RNA expression and CNV from 12 different cancer types were evaluated using information theory. In all cancer types, we looked at the relationship between RNA expression and CNVs. Kinetochore gene expression was found to be substantially linked with CNV levels. In all cancer types, with the exception of thyroid cancer, highly expressed kinetochore genes were enriched in the most dominant cancer-specific co-expression subnetworks characterizing the largest patient subgroups. Except for thyroid cancer, kinetochore inner protein CENPA was among the transcripts most strongly associated with CNV values in all cancer types studied, with significantly higher expression levels in patients with high CNVs than in patients with low CNVs. CENPA function was investigated further in cell models by transfecting genomically stable (HCT116) and unstable (MCF7 and HT29) cancer cell lines using CENPA overexpression vectors. This overexpression increased the number of abnormal cell divisions in the stable cancer cell line HCT116 and, to a lesser extent, in the unstable cell lines MCF7 and HT29. Overexpression improved anchorage-independent growth properties of all cell lines. Our findings suggest that overexpression of kinetochore genes in general, and CENPA in particular, can cause genomic instability and cancer progression.

In Vitro Approaches to Determine the Potential Carcinogenic Risk of Environmental Pollutants

One important environmental/health challenge is to determine, in a feasible way, the potential carcinogenic risk associated with environmental agents/exposures. Since a significant proportion of tumors have an environmental origin, detecting the potential carcinogenic risk of environmental agents is mandatory, as regulated by national and international agencies. The challenge mainly implies finding a way of how to overcome the inefficiencies of long-term trials with rodents when thousands of agents/exposures need to be tested. To such an end, the use of in vitro cell transformation assays (CTAs) was proposed, but the existing prevalidated CTAs do not cover the complexity associated with carcinogenesis processes and present serious limitations. To overcome such limitations, we propose to use a battery of assays covering most of the hallmarks of the carcinogenesis process. For the first time, we grouped such assays as early, intermediate, or advanced biomarkers which allow for the identification of the cells in the initiation, promotion or aggressive stages of tumorigenesis. Our proposal, as a novelty, points out that using a battery containing assays from all three groups can identify if a certain agent/exposure can pose a carcinogenic risk; furthermore, it can gather mechanistic insights into the mode of the action of a specific carcinogen. This structured battery could be very useful for any type of in vitro study, containing human cell lines aiming to detect the potential carcinogenic risks of environmental agents/exposures. In fact, here, we include examples in which these approaches were successfully applied. Finally, we provide a series of advantages that, we believe, contribute to the suitability of our proposed approach for the evaluation of exposure-induced carcinogenic effects and for the development of an alternative strategy for conducting an exposure risk assessment.

Germline Cancer Gene Expression Quantitative Trait Loci Are Associated with Local and Global Tumor Mutations

Somatic mutations drive cancer development and are relevant to patient responses to treatment. Emerging evidence shows that variations in the somatic genome can be influenced by the germline genetic background. However, the mechanisms underlying these germline-somatic associations remain largely obscure. We hypothesized that germline variants can influence somatic mutations in a nearby cancer gene ("local impact") or a set of recurrently mutated cancer genes across the genome ("global impact") through their regulatory effect on gene expression. To test this hypothesis, tumor targeted sequencing data from 12,413 patients across 11 cancer types in the Dana-Farber Profile cohort were integrated with germline cancer gene expression quantitative trait loci (eQTL) from the Genotype-Tissue Expression Project. Variants that upregulate ATM expression were associated with a decreased risk of somatic ATM mutations across 8 cancer types. GLI2, WRN, and CBFB eQTL were associated with global tumor mutational burden of cancer genes in ovarian cancer, glioma, and esophagogastric carcinoma, respectively. An EPHA5 eQTL was associated with mutations in cancer genes specific to colorectal cancer, and eQTL related to expression of APC, WRN, GLI1, FANCA, and TP53 were associated with mutations in genes specific to endometrial cancer. These findings provide evidence that germline-somatic associations are mediated through expression of specific cancer genes, opening new avenues for research on the underlying biological processes.

SIGNIFICANCE

Analysis of associations between the germline genetic background and somatic mutations in patients with cancer suggests that germline variants can influence local and global tumor mutations by altering expression of cancer-related genes. See related commentary by Kar, p. 1165.

Investigating nanoplastics toxicity using advanced stem cell-based intestinal and lung in vitro models

Plastic particles in the nanometer range-called nanoplastics-are environmental contaminants with growing public health concern. As plastic particles are present in water, soil, air and food, human exposure via intestine and lung is unavoidable, but possible health effects are still to be elucidated. To better understand the Mode of Action of plastic particles, it is key to use experimental models that best reflect human physiology. Novel assessment methods like advanced cell models and several alternative approaches are currently used and developed in the scientific community. So far, the use of cancer cell line-based models is the standard approach regarding in vitro nanotoxicology. However, among the many advantages of the use of cancer cell lines, there are also disadvantages that might favor other approaches. In this review, we compare cell line-based models with stem cell-based in vitro models of the human intestine and lung. In the context of nanoplastics research, we highlight the advantages that come with the use of stem cells. Further, the specific challenges of testing nanoplastics in vitro are discussed. Although the use of stem cell-based models can be demanding, we conclude that, depending on the research question, stem cells in combination with advanced exposure strategies might be a more suitable approach than cancer cell lines when it comes to toxicological investigation of nanoplastics.

Molecular characterization based on tumor microenvironment-related signatures for guiding immunotherapy and therapeutic resistance in lung adenocarcinoma

Background: Although the role of tumor microenvironment in lung adenocarcinoma (LUAD) has been explored in a number of studies, the value of TME-related signatures in immunotherapy has not been comprehensively characterized. Materials and Methods: Consensus clustering was conducted to characterize TME-based molecular subtypes using transcription data of LUAD samples. The biological pathways and immune microenvironment were assessed by CIBERSORT, ESTIMATE, and gene set enrichment analysis. A TME-related risk model was established through the algorithms of least absolute shrinkage and selection operator (Lasso) and stepwise Akaike information criterion (stepAIC). Results: Four TME-based molecular subtypes including C1, C2, C3, and C4 were identified, and they showed distinct overall survival, genomic characteristics, DNA methylation pattern, immune microenvironment, and biological pathways. C1 had the worst prognosis and high tumor proliferation rate. C3 and C4 had higher enrichment of anti-tumor signatures compared to C1 and C2. C4 had evidently low enrichment of epithelial-mesenchymal transition (EMT) signature and tumor proliferation rate. C3 was predicted to be more sensitive to immunotherapy compared with other subtypes. C1 is more sensitive to chemotherapy drugs, including Docetaxel, Vinorelbine and Cisplatin, while C3 is more sensitive to Paclitaxel. A five-gene risk model was constructed, which showed a favorable performance in three independent datasets. Low-risk group showed a longer overall survival, more infiltrated immune cells, and higher response to immunotherapy than high-risk group. Conclusion: This study comprehensively characterized the molecular features of LUAD patients based on TME-related signatures, demonstrating the potential of TME-based signatures in exploring the mechanisms of LUAD development. The TME-related risk model was of clinical value to predict LUAD prognosis and guide immunotherapy.

Exposure of Immunogenic Tumor Antigens in Surrendered Immunity and the Significance of Autologous Tumor Cell-Based Vaccination in Precision Medicine

The mechanisms by which immune systems identify and destroy tumors, known as immunosurveillance, have been discussed for decades. However, several factors that lead to tumor persistence and escape from the attack of immune cells in a normal immune system have been found. In the process known as immunoediting, tumors decrease their immunogenicity and evade immunosurveillance. Furthermore, tumors exploit factors such as regulatory T cells, myeloid-derived suppressive cells, and inhibitory cytokines that avoid cytotoxic T cell (CTL) recognition. Current immunotherapies targeting tumors and their surroundings have been proposed. One such immunotherapy is autologous cancer vaccines (ACVs), which are characterized by enriched tumor antigens that can escalate specific CTL responses. Unfortunately, ACVs usually fail to activate desirable therapeutic effects, and the low immunogenicity of ACVs still needs to be elucidated. This difficulty highlights the significance of immunogenic antigens in antitumor therapies. Previous studies have shown that defective host immunity triggers tumor development by reprogramming tumor antigenic expressions. This phenomenon sheds new light on ACVs and provides a potential cue to improve the effectiveness of ACVs. Furthermore, synergistically with the ACV treatment, combinational therapy, which can reverse the suppressive tumor microenvironments, has also been widely proposed. Thus, in this review, we focus on tumor immunogenicity sculpted by the immune systems and discuss the significance and application of restructuring tumor antigens in precision medicine.

Development of genomic instability-associated long non-coding RNA signature: A prognostic risk model of clear cell renal cell carcinoma

Purpose

Renal clear cell carcinoma (ccRCC) is the most lethal of all pathological subtypes of renal cell carcinoma (RCC). Genomic instability was recently reported to be related to the occurrence and development of kidney cancer. The biological roles of long non-coding RNAs (lncRNAs) in tumorigenesis have been increasingly valued, and various lncRNAs were found to be oncogenes or cancer suppressors. Herein, we identified a novel genomic instability-associated lncRNA (GILncs) model for ccRCC patients to predict the overall survival (OS).

Methods

The Cancer Genome Atlas (TCGA) database was utilized to obtain full transcriptome data, somatic mutation profiles, and clinical characteristics. The differentially expressed lncRNAs between the genome-unstable-like group (GU) and the genome-stable-like group (GS) were defined as GILncs, with |logFC| > 1 and an adjusted p-value< 0.05 for a false discovery rate. All samples were allocated into GU-like or GS-like types based on the expression of GILncs observed using hierarchical cluster analyses. A genomic instability-associated lncRNA signature (GILncSig) was constructed using parameters of the included lncRNAs. Quantitative real-time PCR analysis was used to detect the in vitro expression of the included lncRNAs. Validation of the risk model was performed by the log-rank test, time-dependent receiver operating characteristic (ROC) curves analysis, and multivariate Cox regression analysis.

Results

Forty-six lncRNAs were identified as GILncs. LINC00460, AL139351.1, and AC156455.1 were employed for GILncSig calculation based on the results of Cox analysis. GILncSig was confirmed as an independent predictor for OS of ccRCC patients. Additionally, it presented a higher efficiency and accuracy than other RCC prognostic models reported before.

Conclusion

GILncSig score was qualified as a critical indicator, independent of other clinical factors, for prognostic prediction of ccRCC patients.

Characterization of tumor immune microenvironment and cancer therapy for head and neck squamous cell carcinoma through identification of a genomic instability-related lncRNA prognostic signature

Head and neck squamous cell carcinoma (HNSCC) represents one of the most prevalent and malignant tumors of epithelial origins with unfavorable outcomes. Increasing evidence has shown that dysregulated long non-coding RNAs (lncRNAs) correlate with tumorigenesis and genomic instability (GI), while the roles of GI-related lncRNAs in the tumor immune microenvironment (TIME) and predicting cancer therapy are still yet to be clarified. In this study, transcriptome and somatic mutation profiles with clinical parameters were obtained from the TCGA database. Patients were classified into GI-like and genomic stable (GS)-like groups according to the top 25% and bottom 25% cumulative counts of somatic mutations. Differentially expressed lncRNAs (DElncRNAs) between GI- and GS-like groups were identified as GI-related lncRNAs. These lncRNA-related coding genes were enriched in cancer-related KEGG pathways. Patients totaling 499 with clinical information were randomly divided into the training and validation sets. A total of 18 DElncRNAs screened by univariate Cox regression analysis were associated with overall survival (OS) in the training set. A GI-related lncRNA signature that comprised 10 DElncRNAs was generated through least absolute shrinkage and selection operator (Lasso)-Cox regression analysis. Patients in the high-risk group have significantly decreased OS vs. patients in the low-risk group, which was verified in internal validation and entire HNSCC sets. Integrated HNSCC sets from GEO confirmed the notable survival stratification of the signature. The time-dependent receiver operating characteristic curve demonstrated that the signature was reliable. In addition, the signature retained a strong performance of OS prediction for patients with various clinicopathological features. Cell composition analysis showed high anti-tumor immunity in the low-risk group which was evidenced by increased infiltrating CD8+ T cells and natural killer cells and reduced cancer-associated fibroblasts, which was convinced by immune signatures analysis via ssGSEA algorithm. T helper/IFNγ signaling, co-stimulatory, and co-inhibitory signatures showed increased expression in the low-risk group. Low-risk patients were predicted to be beneficial to immunotherapy, which was confirmed by patients with progressive disease who had high risk scores vs. complete remission patients. Furthermore, the drugs that might be sensitive to HNSCC were identified. In summary, the novel prognostic GILncRNA signature provided a promising approach for characterizing the TIME and predicting therapeutic strategies for HNSCC patients.

Novel GIRlncRNA Signature for Predicting the Clinical Outcome and Therapeutic Response in NSCLC

Background: Non–small cell lung cancer (NSCLC) is highly malignant with driver somatic mutations and genomic instability. Long non-coding RNAs (lncRNAs) play a vital role in regulating these two aspects. However, the identification of somatic mutation-derived, genomic instability-related lncRNAs (GIRlncRNAs) and their clinical significance in NSCLC remains largely unexplored.

Methods: Clinical information, gene mutation, and lncRNA expression data were extracted from TCGA database. GIRlncRNAs were screened by a mutator hypothesis-derived computational frame. Co-expression, GO, and KEGG enrichment analyses were performed to investigate the biological functions. Cox and LASSO regression analyses were performed to create a prognostic risk model based on the GIRlncRNA signature (GIRlncSig). The prediction efficiency of the model was evaluated by using correlation analyses with mutation, driver gene, immune microenvironment contexture, and therapeutic response. The prognostic performance of the model was evaluated by external datasets. A nomogram was established and validated in the testing set and TCGA dataset.

Results: A total of 1446 GIRlncRNAs were selected from the screen, and the established GIRlncSig was used to classify patients into high- and low-risk groups. Enrichment analyses showed that GIRlncRNAs were mainly associated with nucleic acid metabolism and DNA damage repair pathways. Cox analyses further identified 19 GIRlncRNAs to construct a GIRlncSig-based risk score model. According to Cox regression and stratification analyses, 14 risk lncRNAs (AC023824.3, AC013287.1, AP000829.1, LINC01611, AC097451.1, AC025419.1, AC079949.2, LINC01600, AC004862.1, AC021594.1, MYRF-AS1, LINC02434, LINC02412, and LINC00337) and five protective lncRNAs (LINC01067, AC012645.1, AL512604.3, AC008278.2, and AC089998.1) were considered powerful predictors. Analyses of the model showed that these GIRlncRNAs were correlated with somatic mutation pattern, immune microenvironment infiltration, immunotherapeutic response, drug sensitivity, and survival of NSCLC patients. The GIRlncSig risk score model demonstrated good predictive performance (AUCs of ROC for 10-year survival was 0.69) and prognostic value in different NSCLC datasets. The nomogram comprising GIRlncSig and tumor stage exhibited improved robustness and feasibility for predicting NSCLC prognosis.

Conclusion: The newly identified GIRlncRNAs are powerful biomarkers for clinical outcome and prognosis of NSCLC. Our study highlights that the GIRlncSig-based score model may be a useful tool for risk stratification and management of NSCLC patients, which deserves further evaluation in future prospective studies.

Identification of the three subtypes and the prognostic characteristics of stomach adenocarcinoma: analysis of the hypoxia-related long non-coding RNAs

Stomach adenocarcinoma (STAD) is one of the most commonly diagnosed cancers. This study analyzed the subtypes and characteristics of STAD subtypes by analyzing hypoxia pathway-related lncRNAs. Potential hub lncRNAs were found and a prognostic model was constructed. Expression profiling data and clinical information of STAD were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Metabolic pathway scores were calculated using single-sample gene set enrichment analysis (ssGSEA) method. Tumor immune microenvironment scores of the samples were assessed by ESTIMATE, MCP-counter, and ssGSEA. Functional analysis of lncRNAs, construction of risk models, and drug sensitivity analysis were performed. Pathway analysis revealed that the hypoxia pathway was a prognostic risk factor. Molecular subtypes were developed based on the hypoxia score-related lncRNAs. Three molecular subtypes (C1, C2, and C3) for gastric STAD were determined. The worst prognosis was in the C2, which was also characterized by the maximum hypoxia pathway-related scores and the maximum immune score. A majority of the immune checkpoints and chemokines were high-expressed in the C2 subtype. Mutations in the C2 subtype were significantly lower than the C1 and C3 subtypes. The subtypes differed in terms of functional and metabolic pathways. Eight hub indicator lncRNAs (MSC-AS1, AC037198.1, LINC00968, AL139393.3, LINC02544, BOLA3-AS1, MIR1915HG, and AC107021.2) capable of predicting patient prognosis were identified. Three hypoxia lncRNA-related molecular subtypes characterized by different prognostic and immune conditions were identified. The results maybe can provide a theoretical basis to improve the clinical diagnosis and treatment of STAD.

Inverse problem approaches for mutation laws in heterogeneous tumours with local and nonlocal dynamics

Cancer cell mutations occur when cells undergo multiple cell divisions, and these mutations can be spontaneous or environmentally-induced. The mechanisms that promote and sustain these mutations are still not fully understood. This study deals with the identification (or reconstruction) of the usually unknown cancer cell mutation law, which lead to the transformation of a primary tumour cell population into a secondary, more aggressive cell population. We focus on local and nonlocal mathematical models for cell dynamics and movement, and identify these mutation laws from macroscopic tumour snapshot data collected at some later stage in the tumour evolution. In a local cancer invasion model, we first reconstruct the mutation law when we assume that the mutations depend only on the surrounding cancer cells (i.e., the ECM plays no role in mutations). Second, we assume that the mutations depend on the ECM only, and we reconstruct the mutation law in this case. Third, we reconstruct the mutation when we assume that there is no prior knowledge about the mutations. Finally, for the nonlocal cancer invasion model, we reconstruct the mutation law that depends on the cancer cells and on the ECM. For these numerical reconstructions, our approximations are based on the finite difference method combined with the finite elements method. As the inverse problem is ill-posed, we use the Tikhonov regularisation technique in order to regularise the solution. Stability of the solution is examined by adding additive noise into the measurements.

Canine transmissible venereal tumour established in immunodeficient mice reprograms the gene expression profiles associated with a favourable tumour microenvironment to enable cancer malignancy

Background

Canine transmissible venereal tumours (CTVTs) can cross the major histocompatibility complex barrier to spread among dogs. In addition to the transmissibility within canids, CTVTs are also known as a suitable model for investigating the tumour–host immunity interaction because dogs live with humans and experience the same environmental risk factors for tumourigenesis. Moreover, outbred dogs are more appropriate than inbred mice models for simulating the diversity of human cancer development. This study built a new model of CTVTs, known as MCTVTs, to further probe the shaping effects of immune stress on tumour development. For xenotransplantation, CTVTs were first injected and developed in immunodeficient mice (NOD.CB17-Prkdc^scid/NcrCrl), defined as XCTVTs. The XCTVTs harvested from NOD/SCID mice were then inoculated and grown in beagles and named mouse xenotransplantation of CTVTs (MCTVTs).

Results

After the inoculation of CTVTs and MCTVTs into immune-competent beagle dogs separately, MCTVTs grew faster and metastasized more frequently than CTVTs did. Gene expression profiles in CTVTs and MCTVTs were analysed by cDNA microarray to reveal that MCTVTs expressed many tumour-promoting genes involved in chronic inflammation, chemotaxis, extracellular space modification, NF-kappa B pathways, and focal adhesion. Furthermore, several well-known tumour-associated biomarkers which could predict tumour progression were overexpressed in MCTVTs.

Conclusions

This study demonstrated that defective host immunity can result in gene instability and enable transcriptome reprogramming within tumour cells. Fast tumour growth in beagle dogs and overexpression of tumour-associated biomarkers were found in a CTVT strain previously established in immunodeficient mice. In addition, dysregulated interaction of chronic inflammation, chemotaxis, and extracellular space modification were revealed to imply the possibly exacerbating mechanisms in the microenvironments of these tumours. In summary, this study offers a potential method to facilitate tumour progression and provide a niche for discovering tumour-associated biomarkers in cancer research.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12917-021-03093-4.

Targeting Chemokine Receptor CCR1 as a Potential Therapeutic Approach for Multiple Myeloma

Multiple myeloma is an incurable plasma B-cell malignancy with 5-year survival rates approximately 10-30% lower than other hematologic cancers. Treatment options include combination chemotherapy followed by autologous stem cell transplantation. However, not all patients are eligible for autologous stem cell transplantation, and current pharmacological agents are limited in their ability to reduce tumor burden and extend multiple myeloma remission times. The "chemokine network" is comprised of chemokines and their cognate receptors, and is a critical component of the normal bone microenvironment as well as the tumor microenvironment of multiple myeloma. Antagonists targeting chemokine-receptor 1 (CCR1) may provide a novel approach for treating multiple myeloma. In vitro CCR1 antagonists display a high degree of specificity, and in some cases signaling bias. In vivo studies have shown they can reduce tumor burden, minimize osteolytic bone damage, deter metastasis, and limit disease progression in multiple myeloma models. While multiple CCR1 antagonists have entered the drug pipeline, none have entered clinical trials for treatment of multiple myeloma. This review will discuss whether current CCR1 antagonists are a viable treatment option for multiple myeloma, and studies aimed at identifying which CCR1 antagonist(s) are most appropriate for this disease.

Obesity and Inflammation: Colorectal Cancer Engines

The prevalence of obesity continues to increase to the extent that it became a worldwide pandemic. An accumulating body of evidence has associated obesity with the development of different types of cancer, including colorectal cancer, which is a notorious disease with a high mortality rate. At the molecular level, colorectal cancer is a heterogenous disease characterized by a myriad of genetic and epigenetic alterations associated with various forms of genomic instability (detailed in Supplementary Materials). Recently, the microenvironment has emerged as a major factor in carcinogenesis. Our aim is to define the different molecular alterations leading to the development of colorectal cancer in obese patients with a focus on the role of the microenvironment in carcinogenesis. We also highlight all existent molecules in clinical trials that target the activated pathways in obesity-associated colorectal cancer, whether used as single treatments or in combination. Obesity predisposes to colorectal cancer via creating a state of chronic inflammation with dysregulated adipokines, inflammatory mediators, and other factors such as immune cell infiltration. A unifying theme in obesity-mediated colorectal cancer is the activation of the PI3K/AKT, mTOR/MAPK, and STAT3 signaling pathways. Different inhibitory molecules towards these pathways exist, increasing the therapeutic choice of obesity-associated colon cancer. However, obese patients are more likely to suffer from chemotherapy overdosing. Preventing obesity through maintaining a healthy and active lifestyle remains to be the best remedy.

Beyond immune checkpoint blockade: emerging immunological strategies

The success of checkpoint inhibitors has accelerated the clinical implementation of a vast mosaic of single agents and combination immunotherapies. However, the lack of clinical translation for a number of immunotherapies as monotherapies or in combination with checkpoint inhibitors has clarified that new strategies must be employed to advance the field. The next chapter of immunotherapy should examine the immuno-oncology therapeutic failures, and consider the complexity of immune cell-cancer cell interactions to better design more effective anticancer drugs. Herein, we briefly review the history of immunotherapy and checkpoint blockade, highlighting important clinical failures. We discuss the critical aspects - beyond T cell co-receptors - of immune processes within the tumour microenvironment (TME) that may serve as avenues along which new therapeutic strategies in immuno-oncology can be forged. Emerging insights into tumour biology suggest that successful future therapeutics will focus on two key factors: rescuing T cell homing and dysfunction in the TME, and reappropriating mononuclear phagocyte function for TME inflammatory remodelling. New drugs will need to consider the complex cell networks that exist within tumours and among cancer types.

Can the Mitochondrial Metabolic Theory Explain Better the Origin and Management of Cancer than Can the Somatic Mutation Theory?

A theory that can best explain the facts of a phenomenon is more likely to advance knowledge than a theory that is less able to explain the facts. Cancer is generally considered a genetic disease based on the somatic mutation theory (SMT) where mutations in proto-oncogenes and tumor suppressor genes cause dysregulated cell growth. Evidence is reviewed showing that the mitochondrial metabolic theory (MMT) can better account for the hallmarks of cancer than can the SMT. Proliferating cancer cells cannot survive or grow without carbons and nitrogen for the synthesis of metabolites and ATP (Adenosine Triphosphate). Glucose carbons are essential for metabolite synthesis through the glycolysis and pentose phosphate pathways while glutamine nitrogen and carbons are essential for the synthesis of nitrogen-containing metabolites and ATP through the glutaminolysis pathway. Glutamine-dependent mitochondrial substrate level phosphorylation becomes essential for ATP synthesis in cancer cells that over-express the glycolytic pyruvate kinase M2 isoform (PKM2), that have deficient OxPhos, and that can grow in either hypoxia (0.1% oxygen) or in cyanide. The simultaneous targeting of glucose and glutamine, while elevating levels of non-fermentable ketone bodies, offers a simple and parsimonious therapeutic strategy for managing most cancers.

Migration and Adhesion of B-Lymphocytes to Specific Microenvironments in Mantle Cell Lymphoma: Interplay between Signaling Pathways and the Epigenetic Landscape

Lymphocyte migration to and sequestration in specific microenvironments plays a crucial role in their differentiation and survival. Lymphocyte trafficking and homing are tightly regulated by signaling pathways and is mediated by cytokines, chemokines, cytokine/chemokine receptors and adhesion molecules. The production of cytokines and chemokines is largely controlled by transcription factors in the context of a specific epigenetic landscape. These regulatory factors are strongly interconnected, and they influence the gene expression pattern in lymphocytes, promoting processes such as cell survival. The epigenetic status of the genome plays a key role in regulating gene expression during many key biological processes, and it is becoming more evident that dysregulation of epigenetic mechanisms contributes to cancer initiation, progression and drug resistance. Here, we review the signaling pathways that regulate lymphoma cell migration and adhesion with a focus on Mantle cell lymphoma and highlight the fundamental role of epigenetic mechanisms in integrating signals at the level of gene expression throughout the genome.

Race as a Contributor to Stromal Modulation of Tumor Progression

Stromal cells play crucial roles in tumor development and are increasingly attractive targets for therapy. There are considerable racial disparities in the incidence and progression of many tumors, reflecting both environmental exposure and genetic differences existing between races. Tumorigenesis and tumor progression are linked to both the propensity to suffer an initiating event and the host response to such an event once it occurs, contributing to incidence and outcomes. In this review, we focused on racial disparities in the tumor microenvironment (TME) of different cancers as potential modulators of growth, metastasis, and response to treatment. Several studies suggest that the TME in AA has a distinct tumor biology and may facilitate both early onset and aggressive tumor growth while inhibiting anti-tumorigenic properties. The TME of AA patients often exhibits an immunosuppressive microenvironment with a substantial enrichment of immune inflammatory pathways and genes. As a result, AA patients can potentially benefit more from treatment strategies that modulate the immune system. Focusing on TME components for diagnostic and therapeutic purposes to address racial disparities is a promising area of investigation. Future basic and clinical research studies on personalized cancer diagnosis and treatment should acknowledge the significance of TME in racial disparities.

Does Cancer Biology Rely on Parrondo's Principles?

Simple Summary

Parrondo’s paradox, whereby losing strategies or deleterious effects can combine to provide a winning outcome, has been increasingly applied by biologists to explain complex adaptations in many living systems. Here, we suggest that considering this paradox in oncology, particularly in relation to the phenotypic diversity of malignant cells, could also be a promising approach to understand several puzzling aspects of cancer biology. For example, the high genetic and epigenetic instability of cancer cells, their metastatic behavior and their capacity to enter dormancy could be explained by Parrondo’s theory. We also discuss the relevance of Parrondo’s paradox in a therapeutical framework using different examples. This work provides a compelling argument that the traditional separation between medicine and other disciplines remains a fundamental limitation that needs to be overcome if complex processes, such as oncogenesis, are to be completely understood.

Abstract

Many aspects of cancer biology remain puzzling, including the proliferative and survival success of malignant cells in spite of their high genetic and epigenetic instability as well as their ability to express migrating phenotypes and/or enter dormancy despite possible fitness loss. Understanding the potential adaptive value of these phenotypic traits is confounded by the fact that, when considered separately, they seem to be rather detrimental at the cell level, at least in the short term. Here, we argue that cancer’s biology and success could frequently be governed by processes underlying Parrondo’s paradox, whereby combinations of intrinsically losing strategies may result in winning outcomes. Oncogenic selection would favor Parrondo’s dynamics because, given the environmental adversity in which malignant cells emerge and evolve, alternating between various less optimal strategies would represent the sole viable option to counteract the changing and deleterious environments cells are exposed to during tumorigenesis. We suggest that malignant processes could be viewed through this lens, and we discuss how Parrondo’s principles are also important when designing therapies against cancer.

Biomechanical Properties of Cancer Cells

Since the crucial role of the microenvironment has been highlighted, many studies have been focused on the role of biomechanics in cancer cell growth and the invasion of the surrounding environment. Despite the search in recent years for molecular biomarkers to try to classify and stratify cancers, much effort needs to be made to take account of morphological and nanomechanical parameters that could provide supplementary information concerning tissue complexity adaptation during cancer development. The biomechanical properties of cancer cells and their surrounding extracellular matrix have actually been proposed as promising biomarkers for cancer diagnosis and prognosis. The present review first describes the main methods used to study the mechanical properties of cancer cells. Then, we address the nanomechanical description of cultured cancer cells and the crucial role of the cytoskeleton for biomechanics linked with cell morphology. Finally, we depict how studying interaction of tumor cells with their surrounding microenvironment is crucial to integrating biomechanical properties in our understanding of tumor growth and local invasion.

An interplay of resource availability, population size and mutation rate potentiates the evolution of metabolic signaling

Background

Asexually reproducing populations of single cells evolve through mutation, natural selection, and genetic drift. Environmental conditions in which the evolution takes place define the emergent fitness landscapes. In this work, we used Avida—a digital evolution framework—to uncover a hitherto unexplored interaction between mutation rates, population size, and the relative abundance of metabolizable resources, and its effect on evolutionary outcomes in small populations of digital organisms.

Results

Over each simulation, the population evolved to one of several states, each associated with a single dominant phenotype with its associated fitness and genotype. For a low mutation rate, acquisition of fitness by organisms was accompanied with, and dependent on, an increase in rate of genomic replication. At an increased mutation rate, phenotypes with high fitness values were similarly achieved through enhanced genome replication rates. In addition, we also observed the frequent emergence of suboptimal fitness phenotype, wherein neighboring organisms signaled to each other information relevant to performing metabolic tasks. This metabolic signaling was vital to fitness acquisition and was correlated with greater genotypic and phenotypic heterogeneity in the population. The frequency of appearance of signaling populations increased with population size and with resource abundance.

Conclusions

Our results reveal a minimal set of environment–genotype interactions that lead to the emergence of metabolic signaling within evolving populations.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12862-021-01782-0.

The immune contexture and Immunoscore in cancer prognosis and therapeutic efficacy

The international American Joint Committee on Cancer/Union for International Cancer Control (AJCC/UICC) tumour-node-metastasis (TNM) staging system provides the current guidelines for the classification of cancer. However, among patients within the same stage, the clinical outcome can be very different. More recently, a novel definition of cancer has emerged, implicating at all stages a complex and dynamic interaction between tumour cells and the immune system. This has enabled the definition of the immune contexture, representing the pre-existing immune parameters associated with patient survival. Even so, the role of distinct immune cell types in modulating cancer progression is increasingly emerging. An immune-based assay named the 'Immunoscore' was defined to quantify the in situ T cell infiltrate and was demonstrated to be superior to the AJCC/UICC TNM classification for patients with colorectal cancer. This Review provides a broad overview of the main immune parameters positively or negatively shaping cancer development, including the Immunoscore, and their prognostic and predictive value. The importance of the immune system in cancer control is demonstrated by the requirement for a pre-existing intratumour adaptive immune response for effective immunotherapies, such as checkpoint inhibitors. Finally, we discuss how the combination of multiple immune parameters, rather than individual ones, might increase prognostic and/or predictive power.

Identification of prognosis-related genes in the tumor microenvironment of stomach adenocarcinoma by TCGA and GEO datasets

Accumulating evidence has demonstrated that tumor microenvironment (TME) plays a crucial role in stomach adenocarcinoma (STAD) development, progression, prognosis and immunotherapeutic responses. How the genes in TME interact and behave is extremely crucial for tumor investigation. In the present study, we used gene expression data of STAD available from TCGA and GEO datasets to infer tumor purity using ESTIMATE algorithms, and predicted the associations between tumor purity and clinical features and clinical outcomes. Next, we calculated the differentially expressed genes (DEGs) from the comparisons of immune and stromal scores, and postulated key biological processes and pathways that the DEGs mainly involved in. Then, we analyzed the prognostic values of DEGs in TCGA dataset, and validated the results by GEO dataset. Finally, we used CIBERSORT computational algorithm to estimate the 22 tumor infiltrating immune cells (TIICs) subsets in STAD tissues. We found that stromal and immune scores were significantly correlated with STAD subtypes, clinical stages, Helicobacter polyri infection, and stromal scores could predict the clinical outcomes in STAD patients. Moreover, we screened 307 common DEGs in TCGA and GSE51105 datasets. In the prognosis analyses, we only found OGN, JAM2, RERG, OLFML2B, and ADAMTS1 genes were significantly associated with overall survival in TCGA and GSE84437 datasets, and these genes were correlated with the fractions of T cells, B cells, macrophages, monocytes, NK cells and DC cells, respectively. Our comprehensive analyses for transcriptional data not only improved the understanding of characteristics of TME, but also provided the targets for individual therapy in STAD.

MYC as a Multifaceted Regulator of Tumor Microenvironment Leading to Metastasis

The Myc family of oncogenes is deregulated in many types of cancer, and their over-expression is often correlated with poor prognosis. The Myc family members are transcription factors that can coordinate the expression of thousands of genes. Among them, c-Myc (MYC) is the gene most strongly associated with cancer, and it is the focus of this review. It regulates the expression of genes involved in cell proliferation, growth, differentiation, self-renewal, survival, metabolism, protein synthesis, and apoptosis. More recently, novel studies have shown that MYC plays a role not only in tumor initiation and growth but also has a broader spectrum of functions in tumor progression. MYC contributes to angiogenesis, immune evasion, invasion, and migration, which all lead to distant metastasis. Moreover, MYC is able to promote tumor growth and aggressiveness by recruiting stromal and tumor-infiltrating cells. In this review, we will dissect all of these novel functions and their involvement in the crosstalk between tumor and host, which have demonstrated that MYC is undoubtedly the master regulator of the tumor microenvironment. In sum, a better understanding of MYC’s role in the tumor microenvironment and metastasis development is crucial in proposing novel and effective cancer treatment strategies.

Recent Advances and Impact of Chemotherapeutic and Antiangiogenic Nanoformulations for Combination Cancer Therapy

Traditional chemotherapy, along with antiangiogenesis drugs (combination cancer therapy), has shown reduced tumor recurrence and improved antitumor effects, as tumor growth and metastasis are often dependent on tumor vascularization. However, the effect of combination chemotherapy, including synergism and additive and even antagonism effects, depends on drug combinations in an optimized ratio. Hence, nanoformulations are ideal, demonstrating a great potential for the combination therapy of chemo-antiangiogenesis for cancer. The rationale for designing various nanocarriers for combination therapy is derived from organic (polymer, lipid), inorganic, or hybrid materials. In particular, hybrid nanocarriers that consist of more than one material construct provide flexibility for different modes of entrapment within the same carrier—e.g., physical adsorption, encapsulation, and chemical conjugation strategies. These multifunctional nanocarriers can thus be used to co-deliver chemo- and antiangiogenesis drugs with tunable drug release at target sites. Hence, this review attempts to survey the most recent advances in nanoformulations and their impact on cancer treatment in a combined regimen—i.e., conventional cytotoxic and antiangiogenesis agents. The mechanisms and site-specific co-delivery strategies are also discussed herein, along with future prospects.

C-C motif chemokine 14 as a novel potential biomarker for predicting the prognosis of epithelial ovarian cancer

Previous studies have demonstrated that C-C motif chemokine 14 (CCL14) plays an important role in the occurrence and development of cancer. However, the significance of CCL14 in the progression and prognosis of epithelial ovarian cancer (EOC) has not yet been reported. The standard EnVision procedure for tissue microarrays was used to evaluate the immunohistochemical expression of CCL14 protein in 154 patients with EOC who underwent tumor-debulking operations at the Central Cancer Department of Sun Yat-Sen University (Guangzhou, China) or Jiangmen Central Hospital (Jiangmen, China). The association between CCL14 expression and clinicopathological variables was assessed using the χ² test. For survival status of patients with EOC, Kaplan-Meier survival analysis and a Cox multivariate regression model was used. Expression of CCL14 protein was significantly associated with International Federation of Gynecology and Obstetric stage (P=0.014) and pN status(P=0.005). Kaplan-Meier survival analysis revealed that the survival time of patients with high expression of CCL14 was 136.1 months and that of patients with low expression of CCL14 was 98.9 months (P=0.026). Multivariate analysis demonstrated that CCL14 upregulation was associated with overall survival time (HR, 0.48; 95% CI, 0.261–0.896; P=0.021) and progression-free survival time (HR,0.437; 95% CI, 0.228–0.839; P=0.013). In conclusion, CCL14 is an independent prognostic factor for EOC and upregulation of CCL14 is associated with a more favorable prognosis in patients with EOC.