scholarly journals Assessing the contribution of tumor mutational phenotypes to cancer progression risk

2021 ◽  
Vol 17 (3) ◽  
pp. e1008777
Author(s):  
Yifeng Tao ◽  
Ashok Rajaraman ◽  
Xiaoyue Cui ◽  
Ziyi Cui ◽  
Haoran Chen ◽  
...  
Keyword(s):  
Cancer Progression ◽  
Predictive Power ◽  
Clonal Evolution ◽  
Large Fraction ◽  
Disease Free Survival ◽  
Tumor Evolution ◽  
Driver Gene ◽  
Learning Framework ◽  
Tree Inference ◽  
Progression Risk

Cancer occurs via an accumulation of somatic genomic alterations in a process of clonal evolution. There has been intensive study of potential causal mutations driving cancer development and progression. However, much recent evidence suggests that tumor evolution is normally driven by a variety of mechanisms of somatic hypermutability, which act in different combinations or degrees in different cancers. These variations in mutability phenotypes are predictive of progression outcomes independent of the specific mutations they have produced to date. Here we explore the question of how and to what degree these differences in mutational phenotypes act in a cancer to predict its future progression. We develop a computational paradigm using evolutionary tree inference (tumor phylogeny) algorithms to derive features quantifying single-tumor mutational phenotypes, followed by a machine learning framework to identify key features predictive of progression. Analyses of breast invasive carcinoma and lung carcinoma demonstrate that a large fraction of the risk of future clinical outcomes of cancer progression—overall survival and disease-free survival—can be explained solely from mutational phenotype features derived from the phylogenetic analysis. We further show that mutational phenotypes have additional predictive power even after accounting for traditional clinical and driver gene-centric genomic predictors of progression. These results confirm the importance of mutational phenotypes in contributing to cancer progression risk and suggest strategies for enhancing the predictive power of conventional clinical data or driver-centric biomarkers.

scholarly journals Improving personalized prediction of cancer prognoses with clonal evolution models

2019 ◽  
Author(s):  
Yifeng Tao ◽  
Ashok Rajaraman ◽  
Xiaoyue Cui ◽  
Ziyi Cui ◽  
Jesse Eaton ◽  
...  
Keyword(s):  
Cancer Progression ◽  
Predictive Power ◽  
Clonal Evolution ◽  
Disease Free Survival ◽  
Lung Squamous Cell Carcinoma ◽  
Predictive Biomarkers ◽  
Tumor Evolution ◽  
Structural Variations ◽  
Genomic Alterations ◽  
Tree Inference

AbstractCancer occurs via an accumulation of somatic genomic alterations in a process of clonal evolution. There has been intensive study of potential causal mutations driving cancer development and progression. However, much recent evidence suggests that tumor evolution is normally driven by a variety of mechanisms of somatic hypermutability, known as mutator phenotypes, which act in different combinations or degrees in different cancers. Here we explore the question of how and to which degree different mutator phenotypes act in a cancer predict its future progression. We develop a computational paradigm using evolutionary tree inference (tumor phylogeny) algorithms to derive features quantifying single-tumor mutational preferences, followed by a machine learning frame-work to identify key features predictive of progression. We build phylogenies tracing the evolution of subclones of cells in tumor tissues using a variety of somatic genomic alterations, including single nucleotide variations, copy number alterations, and structural variations. We demonstrate that mutation preference features derived from the phylogenies are predictive of clinical outcomes of cancer progression – overall survival and disease-free survival – based on the analyses on breast invasive carcinoma, lung adenocarcinoma, and lung squamous cell carcinoma. We further show that mutational phenotypes have predictive power even after accounting for traditional clinical and driver-centric predictors of progression. These results confirm the power of mutational phenotypes as an independent class of predictive biomarkers and suggest a strategy for enhancing the predictive power of conventional clinical or driver-centric genomic features.

Measuring parameters of the cancer ecosystem for cancer ecological staging.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e14684-e14684
Author(s):  
James R. Cunningham ◽  
Jon Rittenbach ◽  
Mitch Clemens ◽  
Cheryl Dodd ◽  
Ashley Wilson ◽  
...  
Keyword(s):  
Cancer Progression ◽  
Clonal Evolution ◽  
Genetic Selection ◽  
Staging System ◽  
Patient Questionnaire ◽  
Tumor Evolution ◽  
Cancer Evolution ◽  
Level Of Selection ◽  
Ecological Profiles ◽  
Active Cancer

e14684 Background: Cancer progression through clonal evolution and emergent phenotypic heterogeneity is thought to reflect stochastic events such as genetic drift. This divergence over time in the character of a neoplasm might also reflect genetic selection, analogous to other populations in nature, to maximize niche resource utilization. We hypothesized that selection pressures operate in patients with cancer to drive cancer evolution, are clinically identifiable, their influence measurable. Methods: To develop a system for cancer ecology staging, a feasibility study recruited 15 patients with active cancer from any site, with expected survival of more than 6 months and providing informed consent. A set of clinical parameters obtained from a patient questionnaire, physical exam and laboratory testing was used to generate eight separate ecological profiles of tumor microenvironment, chronic inflammation, energy balance, psychosocial stress, GI microbiome, endocrine environment, skeletal remodeling and environmental mutagenesis. A scoring system, based on evidence of positive selection was designed to quantitate the individual profiles. Profile scores were then aggregated using a 2-D radar plot to generate a polygon, an ‘ecogram’, whose area, it is hypothesized, corresponds to the net level of selection pressure influencing tumor evolution. Results: Ecological profiles were obtained from each of 15 patients allowing determination of the ecogram area (EA) bounded by the polygon. EA determinations ranged widely among the 15 patient, from 0-12.7 arbitrary units (au, mean 5.01± 0.80). Ecograms from individual patients demonstrated unique shapes suggesting specificity for individual patient ecology. EA measurements were then used to inform an ecological staging system based on a simplified dichotomization, low/high, of ecosystem resources and threats. Of 15 patients, 6 were considered to have high resources (EA > 5au) available to support tumor evolution. High anti-tumor threat, measured by CD3 lymphocyte immunohistochemical scoring, was detected in 11 patients. Conclusions: An ecological assessment of patients with active cancer appears feasible. Inter-patient variation in ecogram area and morphology suggests there are potential important differences in genetic selection found between patients and should be correlated with survival outcomes in future studies, validation offering a target for ecosystem ‘restoration’.

scholarly journals The genomic and epigenomic evolutionary history of papillary renal cell carcinomas

2018 ◽  
Author(s):  
Bin Zhu ◽  
Maria Luana Poeta ◽  
Manuela Costantini ◽  
Tongwu Zhang ◽  
Jianxin Shi ◽  
...  
Keyword(s):  
Kidney Cancer ◽  
Renal Cell ◽  
Large Scale ◽  
Clonal Evolution ◽  
Prognostic Significance ◽  
Intratumor Heterogeneity ◽  
Tumor Evolution ◽  
Driver Gene ◽  
Renal Cell Carcinomas ◽  
Cancer Subtypes

ABSTRACTIntratumor heterogeneity (ITH) and tumor evolution have been well described for clear cell renal cell carcinomas (ccRCC), but they are less studied for other kidney cancer subtypes. Here we investigate ITH and clonal evolution of papillary renal cell carcinoma (pRCC) and rarer kidney cancer subtypes, integrating whole-genome sequencing and DNA methylation data. In 29 tumors, up to 10 samples from the center to the periphery of each tumor, and metastatic samples in 2 cases, enable phylogenetic analysis of spatial features of clonal expansion, which shows congruent patterns of genomic and epigenomic evolution. In contrast to previous studies of ccRCC, in pRCC driver gene mutations and most arm-level somatic copy number alterations (SCNAs) are clonal. These findings suggest that a single biopsy would be sufficient to identify the important genetic drivers and targeting large-scale SCNAs may improve pRCC treatment, which is currently poor. While type 1 pRCC displays near absence of structural variants (SVs), the more aggressive type 2 pRCC and the rarer subtypes have numerous SVs, which should be pursued for prognostic significance.

scholarly journals Interleukin-33-Enhanced CXCR4 Signaling Circuit Mediated by Carcinoma-Associated Fibroblasts Promotes Invasiveness of Head and Neck Cancer

Cancers ◽  
2021 ◽  
Vol 13 (14) ◽  
pp. 3442
Author(s):  
Yu-Chun Lin ◽  
Wen-Yen Huang ◽  
Tsai-Yu Lee ◽  
Yi-Ming Chang ◽  
Su-Feng Chen ◽  
...  
Keyword(s):  
Head And Neck ◽  
Cancer Cell ◽  
Cancer Progression ◽  
Molecular Mechanisms ◽  
Disease Free Survival ◽  
Interleukin 33 ◽  
Cxcr4 Signaling ◽  
Regulatory Circuit ◽  
Carcinoma Associated Fibroblasts ◽  
Self Production

Despite recent advances, treatment for head and neck squamous cell carcinoma (HNSCC) has limited efficacy in preventing tumor progression. We confirmed previously that carcinoma-associated fibroblasts (CAF)-induced interleukin-33 (IL-33) contributed to cancer progression. However, the molecular mechanisms underlying the complex communication network of the tumor microenvironment merited further evaluation. To simulate the IL-33-induced autocrine signaling, stable clones of IL-33-overexpressing HNSCC cells were established. Besides well-established IL-33/ST2 and SDF1/CXCR4 (stromal-derived factor 1/C-X-C motif chemokine receptor 4) signaling, the CAF-induced IL-33 upregulated CXCR4 via cancer cell induction of IL-33 self-production. The IL-33-enhanced-CXCR4 regulatory circuit involves SDF1/CXCR4 signaling activation and modulates tumor behavior. An in vivo study confirmed the functional role of IL-33/CXCR4 in tumor initiation and metastasis. The CXCR4 and/or IL-33 blockade reduced HNSCC cell aggressiveness, with attenuated invasions and metastases. Immunohistochemistry confirmed that IL-33 and CXCR4 expression correlated significantly with disease-free survival and IL-33-CXCR4 co-expression predicted a poor outcome. Besides paracrine signaling, the CAF-induced IL-33 reciprocally enhanced the autocrine cancer-cell self-production of IL-33 and the corresponding CXCR4 upregulation, leading to the activation of SDF1/CXCR4 signaling subsequent to cancer progression. Thus, targeting the IL-33-enhanced-CXCR4 regulatory circuit attenuates tumor aggressiveness and provides a potential therapeutic option for improving the prognosis in HNSCC patients.

scholarly journals Clinical and prognostic significances of cancer stem cell markers in gastric cancer patients: a systematic review and meta-analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Mahdieh Razmi ◽  
Roya Ghods ◽  
Somayeh Vafaei ◽  
Maryam Sahlolbei ◽  
Leili Saeednejad Zanjani ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Stem Cell ◽  
Cancer Stem Cell ◽  
Clinical Outcomes ◽  
Cancer Progression ◽  
Poor Prognosis ◽  
Meta Analysis ◽  
Disease Free Survival ◽  
Stem Cell Markers ◽  
Free Survival

Abstract Background Gastric cancer (GC) is considered one of the most lethal malignancies worldwide, which is accompanied by a poor prognosis. Although reports regarding the importance of cancer stem cell (CSC) markers in gastric cancer progression have rapidly developed over the last few decades, their clinicopathological and prognostic values in gastric cancer still remain inconclusive. Therefore, the current meta-analysis aimed to quantitatively re-evaluate the association of CSC markers expression, overall and individually, with GC patients’ clinical and survival outcomes. Methods Literature databases including PubMed, Scopus, ISI Web of Science, and Embase were searched to identify the eligible articles. Hazard ratios (HRs) or odds ratios (ORs) with 95% confidence intervals (CIs) were recorded or calculated to determine the relationships between CSC markers expression positivity and overall survival (OS), disease-free survival (DFS)/relapse-free survival (RFS), disease-specific survival (DSS)/ cancer-specific survival (CSS), and clinicopathological features. Results We initially retrieved 4,425 articles, of which a total of 66 articles with 89 studies were considered as eligible for this meta-analysis, comprising of 11,274 GC patients. Overall data analyses indicated that the overexpression of CSC markers is associated with TNM stage (OR = 2.19, 95% CI 1.84–2.61, P = 0.013), lymph node metastasis (OR = 1.76, 95% CI 1.54–2.02, P < 0.001), worse OS (HR = 1.65, 95% CI 1.54–1.77, P < 0.001), poor CSS/DSS (HR = 1.69, 95% CI 1.33–2.15, P < 0.001), and unfavorable DFS/RFS (HR = 2.35, 95% CI 1.90–2.89, P < 0.001) in GC patients. However, CSC markers expression was found to be slightly linked to tumor differentiation (OR = 1.25, 95% CI 1.01–1.55, P = 0.035). Sub-analysis demonstrated a significant positive relationship between most of the individual markers, specially Gli-1, Oct-4, CD44, CD44V6, and CD133, and clinical outcomes as well as the reduced survival, whereas overexpression of Lgr-5, Nanog, and sonic hedgehog (Shh) was not found to be related to the majority of clinical outcomes in GC patients. Conclusion The expression of CSC markers is mostly associated with worse outcomes in patients with GC, both overall and individual. The detection of a combined panel of CSC markers might be appropriate as a prognostic stratification marker to predict tumor aggressiveness and poor prognosis in patients with GC, which probably results in identifying novel potential targets for therapeutic approaches.

scholarly journals CCL20/TNF/VEGFA Cytokine Secretory Phenotype of Tumor-Associated Macrophages Is a Negative Prognostic Factor in Cutaneous Melanoma

Cancers ◽  
2021 ◽  
Vol 13 (16) ◽  
pp. 3943
Author(s):  
Alba Gutiérrez-Seijo ◽  
Elena García-Martínez ◽  
Celia Barrio-Alonso ◽  
Miriam Pareja-Malagón ◽  
Alejandra Acosta-Ocampo ◽  
...  
Keyword(s):  
Cutaneous Melanoma ◽  
Large Fraction ◽  
Prognostic Significance ◽  
Disease Free Survival ◽  
Rna Seq ◽  
Primary Cutaneous Melanoma ◽  
Kaplan Meier ◽  
Intracellular Cytokines ◽  
Negative Prognostic Factor

TAMs constitute a large fraction of infiltrating immune cells in melanoma tissues, but their significance for clinical outcomes remains unclear. We explored diverse TAM parameters in clinically relevant primary cutaneous melanoma samples, including density, location, size, and polarization marker expression; in addition, because cytokine production is a hallmark of macrophages function, we measured CCL20, TNF, and VEGFA intracellular cytokines by single-cell multiparametric confocal microscopy. The Kaplan–Meier method was used to analyze correlation with melanoma-specific disease-free survival and overall survival. No significant correlations with clinical parameters were observed for TAM density, morphology, or location. Significantly, higher contents of the intracellular cytokines CCL20, TNF, and VEGFA were quantified in TAMs infiltrating metastasizing compared to non-metastasizing skin primary melanomas (p < 0.001). To mechanistically explore cytokine up-regulation, we performed in vitro studies with melanoma-conditioned macrophages, using RNA-seq to explore involved pathways and specific inhibitors. We show that p53 and NF-κB coregulate CCL20, TNF, and VEGFA in melanoma-conditioned macrophages. These results delineate a clinically relevant pro-oncogenic cytokine profile of TAMs with prognostic significance in primary melanomas and point to the combined therapeutic targeting of NF-kB/p53 pathways to control the deviation of TAMs in melanoma.

scholarly journals Interleukin-35 Expression in Non-Small Cell Lung Cancer is Associated with Tumor Progression

2018 ◽  
Vol 51 (4) ◽  
pp. 1839-1851 ◽  
Author(s):  
Mingfei Sun ◽  
Xianjie Zheng ◽  
Qingjiang Meng ◽  
Yanjun Dong ◽  
Guoyu Zhang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cancer Progression ◽  
Cell Lung Cancer ◽  
Disease Free Survival ◽  
Prognostic Indicator ◽  
Small Cell ◽  
Inflammatory Factor ◽  
Small Cell Lung ◽  
Chemotherapy Drugs

Background/Aims: Lung cancer continues to be the leading cause of cancer related deaths worldwide due to its high incidence, malignant behavior and lack of major advancements in treatment strategy. The occurrence and development of lung cancer is closely related to inflammation. Thus, we conducted the present study to investigate the effects of IL-35 (Interleukin 35), a newly identified anti-inflammatory factor, on non-small cell lung cancer (NSCLC), which accounts for about 85% of all lung cancers. Methods: We first evaluated the IL-35 expression in 384 pairs of NSCLC samples and their adjacent normal mucosa by realtime PCR, ELISA (Enzyme-linked immunoassay) and tissue microarrays. Then the role of IL-35 on patient survival rates, cancer progression and their sensitivity to chemotherapy drugs were assessed. Results: IL-35 was barely expressed in the NSCLC tissues but highly expressed in the adjacent normal tissues. The down-regulation of IL-35 was significantly correlated with the results of American Joint Committee on Cancer stage, differentiation and it was also shown to be an independent prognostic indicator of disease-free survival and overall survival for patients with NSCLC. Overexpression of IL-35 in NSCLC cells suppressed cell migration, invasion, proliferation, colony formation through suppressing β-catenin. IL-35 inhibited NSCLC formation in the mice model and sensitize the cancer cells to chemotherapy drugs. Conclusion: Our results showed that IL-35 plays an inhibitory role in NSCLC development and function as a novel prognostic indicator and a potential therapeutic target.

scholarly journals GLRX3, a novel cancer stem cell-related secretory biomarker of pancreatic ductal adenocarcinoma

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Jung Hyun Jo ◽  
Sun A Kim ◽  
Jeong Hoon Lee ◽  
Yu Rang Park ◽  
Chanyang Kim ◽  
...  
Keyword(s):  
Pancreatic Ductal Adenocarcinoma ◽  
Cancer Progression ◽  
Biomarker Discovery ◽  
Disease Free Survival ◽  
Tumor Formation ◽  
Ductal Adenocarcinoma ◽  
Curative Surgery ◽  
In Vitro Proliferation

Abstract Background Cancer stem cells (CSCs) are implicated in carcinogenesis, cancer progression, and recurrence. Several biomarkers have been described for pancreatic ductal adenocarcinoma (PDAC) CSCs; however, their function and mechanism remain unclear. Method In this study, secretome analysis was performed in pancreatic CSC-enriched spheres and control adherent cells for biomarker discovery. Glutaredoxin3 (GLRX3), a novel candidate upregulated in spheres, was evaluated for its function and clinical implication. Results PDAC CSC populations, cell lines, patient tissues, and blood samples demonstrated GLRX3 overexpression. In contrast, GLRX3 silencing decreased the in vitro proliferation, migration, clonogenicity, and sphere formation of cells. GLRX3 knockdown also reduced tumor formation and growth in vivo. GLRX3 was found to regulate Met/PI3K/AKT signaling and stemness-related molecules. ELISA results indicated GLRX3 overexpression in the serum of patients with PDAC compared to that in healthy controls. The sensitivity and specificity of GLRX3 for PDAC diagnosis were 80.0 and 100%, respectively. When GLRX3 and CA19–9 were combined, sensitivity was significantly increased to 98.3% compared to that with GLRX3 or CA19–9 alone. High GLRX3 expression was also associated with poor disease-free survival in patients receiving curative surgery. Conclusion Overall, these results indicate GLRX3 as a novel diagnostic marker and therapeutic target for PDAC targeting CSCs.

scholarly journals NR5A2 Is One of 12 Transcription Factors Predicting Prognosis in HNSCC and Regulates Cancer Cell Proliferation in a p53-Dependent Manner

2021 ◽  
Vol 11 ◽  
Author(s):  
Kun Zhang ◽  
Ming Xiao ◽  
Xin Jin ◽  
Hongyan Jiang
Keyword(s):  
Overall Survival ◽  
Survival Time ◽  
Cancer Progression ◽  
Risk Model ◽  
Critical Role ◽  
Disease Free Survival ◽  
Dependent Manner ◽  
Loss Of Function ◽  
Free Survival ◽  
Disease Free

Head and neck squamous cell carcinoma (HNSCC) rank seventh among the most common type of malignant tumor worldwide. Various evidences suggest that transcriptional factors (TFs) play a critical role in modulating cancer progression. However, the prognostic value of TFs in HNSCC remains unclear. Here, we identified a risk model based on a 12-TF signature to predict recurrence-free survival (RFS) in patients with HNSCC. We further analyzed the ability of the 12-TF to predict the disease-free survival time and overall survival time in HNSCC, and found that only NR5A2 down-regulation was strongly associated with shortened overall survival and disease-free survival time in HNSCC. Moreover, we systemically studied the role of NR5A2 in HNSCC and found that NR5A2 regulated HNSCC cell growth in a TP53 status-dependent manner. In p53 proficient cells, NR5A2 knockdown increased the expression of TP53 and activated the p53 pathway to enhance cancer cells proliferation. In contrast, NR5A2 silencing suppressed the growth of HNSCC cells with p53 loss/deletion by inhibiting the glycolysis process. Therefore, our results suggested that NR5A2 may serve as a promising therapeutic target in HNSCC harboring loss-of-function TP53 mutations.

scholarly journals Molecular Profiles of Matched Primary and Metastatic Tumor Samples Support a Linear Evolutionary Model of Breast Cancer

2019 ◽  
Author(s):  
Runpu Chen ◽  
Steve Goodison ◽  
Yijun Sun
Keyword(s):  
Breast Cancer ◽  
Cancer Progression ◽  
Evolutionary Model ◽  
Metastatic Tumor ◽  
Cancer Diagnostics ◽  
Tumor Evolution ◽  
Paired Data ◽  
Cancer Subtypes ◽  
Cancer Data ◽  
Progression Model

AbstractThe interpretation of accumulating genomic data with respect to tumor evolution and cancer progression requires integrated models. We developed a computational approach that enables the construction of disease progression models using static sample data. Application to breast cancer data revealed a linear, branching evolutionary model with two distinct trajectories for malignant progression. Here, we used the progression model as a foundation to investigate the relationships between matched primary and metastasis breast tumor samples. Mapping paired data onto the model confirmed that molecular breast cancer subtypes can shift during progression, and supported directional tumor evolution through luminal subtypes to increasingly malignant states. Cancer progression modeling through the analysis of available static samples represents a promising breakthrough. Further refinement of a roadmap of breast cancer progression will facilitate the development of improved cancer diagnostics, prognostics and targeted therapeutics.

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