scholarly journals Heterogenous Profiles Between Matched Primary Tumors and Brain Metastases Reveal Tumor Evolution

2021 ◽  
Author(s):  
Yanming Chen ◽  
Xiaoxiao Dai ◽  
Ji Wang ◽  
Chuming Tao ◽  
Ye Wang ◽  
...  
Keyword(s):  
Brain Metastases ◽  
Tumor Heterogeneity ◽  
Spatial Diversity ◽  
Immune Checkpoints ◽  
Tumor Evolution ◽  
Single Patient ◽  
Molecular Phenotype ◽  
Primary Tumors ◽  
Patient Level ◽  
Temporal And Spatial

Abstract Background: Brain metastases (BMs) are the most common central nervous system (CNS) malignant tumors, with rapid disease progression and extremely poor prognosis. The heterogeneity between primary tumors and BMs leads to the divergent efficacy of the adjuvant therapy response to primary tumors and BMs. However, the extent of heterogeneity between primary tumors and BMs, and the evolutionary process remains little known. Methods: To deeply insight the extent of inter-tumor heterogeneity at single-patient level and the process of these evolutions, we retrospectively analyzed a total of 26 tumor samples from 11 patients with matched primary tumors and BMs. One patient underwent four times brain metastatic lesion surgery with diverse locations and one operation for the primary lesion. The genomic and immune heterogeneity between primary tumors and BMs was evaluated by utilizing the whole-exome sequencing (WESeq) and immunohistochemical analysis.Results: In addition to inheriting genomic phenotype and molecular phenotype from the primary tumors, massive unique genomic phenotype and molecular phenotype were also observed in BMs, which revealed unimaginable complexity of tumor evolution and extensive heterogeneity among lesions at single-patient level. Our study also verified that the expression level of immune checkpoints-related molecule Programmed Death-Ligand 1 (PD-L1) (P = 0.0013) and the density of tumor-infiltrating lymphocytes (TILs) (P = 0.0248) in BMs were significantly lower than that in paired primary tumors. Additionally, tumor microvascular density (MVD) and tumor invasiveness were also differed between primary tumors and paired BMs, indicating that temporal and spatial diversity profoundly contributes to the evolution of BMs heterogeneity.Conclusion: We verified the significance of temporal and spatial factors to the evolution of tumor heterogeneity by multi-dimensional analysis of matched primary tumors and BMs, which also provided novel insight for formulating individualized treatment strategies of BMs.

Gamma Knife surgery as sole treatment for multiple brain metastases: 2-center retrospective review of 1508 cases meeting the inclusion criteria of the JLGK0901 multi-institutional prospective study

2010 ◽  
Vol 113 (Special_Supplement) ◽  
pp. 48-52 ◽  
Author(s):  
Toru Serizawa ◽  
Masaaki Yamamoto ◽  
Yasunori Sato ◽  
Yoshinori Higuchi ◽  
Osamu Nagano ◽  
...  
Keyword(s):  
Brain Metastases ◽  
Gamma Knife ◽  
Class Ii ◽  
Hazard Ratio ◽  
Gamma Knife Surgery ◽  
Inclusion Criteria ◽  
Primary Tumors ◽  
Poor Prognostic Factor ◽  
Group A ◽  
Group B

Object The authors retrospectively reviewed the results of Gamma Knife surgery (GKS) used as the sole treatment for brain metastases in patients who met the eligibility criteria for the ongoing JLGK0901 multi-institutional prospective trial. They also discuss the anticipated results of the JLGK0901 study. Methods Data from 1508 consecutive cases were analyzed. All of the patients were treated at the Gamma Knife House of Chiba Cardiovascular Center or the Mito Gamma House of Katsuta Hospital between 1998 and 2007 and met the following JLGK0901 inclusion criteria: 1) newly diagnosed brain metastases, 2) 1–10 brain lesions, 3) less than 10 cm3 volume of the largest tumor, 4) no more than 15 cm3 total tumor volume, 5) no findings of CSF dissemination, and 6) no impairment of activities of daily living (Karnofsky Performance Scale score < 70) due to extracranial disease. At the initial treatment, all visible lesions were irradiated with GKS without upfront whole-brain radiation therapy. Thereafter, gadolinium-enhanced MR imaging was performed every 2–3 months, and new distant lesions were appropriately retreated with GKS. Patients were divided into groups according to numbers of tumors: Group A, single lesions (565 cases); Group B, 2–4 tumors (577 cases); and Group C, 5–10 tumors (366 cases). The differences in overall survival (OS) were compared between groups. Results The median age of the patients was 66 years (range 19–96 years). There were 963 men and 545 women. The primary tumors were in the lung in 1114 patients, gastrointestinal tract in 179, breast in 105, urinary tract in 66, and other sites in 44. The overall mean survival time was 0.78 years (0.99 years for Group A, 0.68 years for Group B, and 0.62 years for Group C). The differences between Groups A and B (p < 0.0001) and between Groups B and C (p = 0.0312) were statistically significant. Multivariate analysis revealed significant prognostic factors for OS to be sex (poor prognostic factor: male, p < 0.0001), recursive partitioning analysis class (Class I vs Class II and Class II vs III, both p < 0.0001), primary site (lung vs breast, p = 0.0047), and number of tumors (Group A vs Group B, p < 0.0001). However, no statistically difference was detected between Groups B and C (p = 0.1027, hazard ratio 1.124, 95% CI 0.999–1.265). Conclusions The results of this retrospective analysis revealed an upper CI of 1.265 for the hazard ratio, which was lower than the 1.3 initially set by the JLGK0901 study. The JLGK0901 study is anticipated to show noninferiority of GKS as sole treatment for patients with 5–10 brain metastases compared with those with 2–4 in terms of OS.

Gamma Knife surgery for metastatic brain tumors

2008 ◽  
Vol 109 (Supplement) ◽  
pp. 118-121 ◽  
Author(s):  
Toru Serizawa ◽  
Masaaki Yamamoto ◽  
Osamu Nagano ◽  
Yoshinori Higuchi ◽  
Shinji Matsuda ◽  
...  
Keyword(s):  
Brain Metastases ◽  
Gamma Knife ◽  
Patient Selection ◽  
Selection Criterion ◽  
Gamma Knife Surgery ◽  
Treatment Result ◽  
Karnofsky Performance Scale ◽  
Consecutive Series ◽  
Primary Tumors ◽  
Patient Selection Criterion

Object The authors compared results of Gamma Knife surgery (GKS) for brain metastases obtained at 2 institutions in Japan. Methods They analyzed a consecutive series of 2390 patients with brain metastases who underwent GKS from 1998 through 2005 in 2 institutes (1181 patients in Chiba; 1209 in Mito). In the 2 facilities, 1 neurosurgeon each was responsible for diagnosis, patient selection, GKS procedures, and follow-up (T.S. in Chiba, M.Y. in Mito). Even if tumor numbers exceeded 4, all visible lesions were irradiated with a total skull integral dose (TSID) of ≤ 10–12 J. No prophylactic whole-brain radiotherapy (WBRT) was applied. If new distant lesions were detected, salvage GKS was appropriately performed. Results The distributions of patient and treatment factors did not differ between institutes. The most common primary tumors were lung cancer (1572 patients), followed by gastrointestinal tract (316), breast (211), kidney (113), and other cancers (159). The median survival periods were 7.7 months in Chiba and 7.0 months in Mito (p = 0.0635). The significant poor prognostic factors for overall survival were active extracranial disease status, male sex, and low initial Karnofsky Performance Scale score on multivariate analysis (all p < 0.0001). The neurological survival rates at 1 year were 86.6% in Chiba and 84.2% in Mito (p = 0.3310). Conclusions This 2-institute study demonstrated no significant institutional differences in any of the treatment result items. Gamma Knife surgery for brain metastases without prophylactic WBRT prevents neurological death and allows a patient to maintain good brain condition. However, there is 1 important patient selection criterion: regardless of how many tumors there are, all lesions can be irradiated with a TSID of ≤12 J.

scholarly journals Metastatic heterogeneity of the consensus molecular subtypes of colorectal cancer

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Peter W. Eide ◽  
Seyed H. Moosavi ◽  
Ina A. Eilertsen ◽  
Tuva H. Brunsell ◽  
Jonas Langerud ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Principal Components ◽  
Prognostic Value ◽  
Tumor Heterogeneity ◽  
Molecular Subtypes ◽  
R Package ◽  
Data Set ◽  
Primary Tumors ◽  
External Data

AbstractGene expression-based subtypes of colorectal cancer have clinical relevance, but the representativeness of primary tumors and the consensus molecular subtypes (CMS) for metastatic cancers is not well known. We investigated the metastatic heterogeneity of CMS. The best approach to subtype translation was delineated by comparisons of transcriptomic profiles from 317 primary tumors and 295 liver metastases, including multi-metastatic samples from 45 patients and 14 primary-metastasis sets. Associations were validated in an external data set (n = 618). Projection of metastases onto principal components of primary tumors showed that metastases were depleted of CMS1-immune/CMS3-metabolic signals, enriched for CMS4-mesenchymal/stromal signals, and heavily influenced by the microenvironment. The tailored CMS classifier (available in an updated version of the R package CMScaller) therefore implemented an approach to regress out the liver tissue background. The majority of classified metastases were either CMS2 or CMS4. Nonetheless, subtype switching and inter-metastatic CMS heterogeneity were frequent and increased with sampling intensity. Poor-prognostic value of CMS1/3 metastases was consistent in the context of intra-patient tumor heterogeneity.

scholarly journals Patient-derived models of brain metastases recapitulate the histopathology and biology of human metastatic cancers

2020 ◽  
Author(s):  
Claudia C. Faria ◽  
Carlos Custódia ◽  
Rita Cascão ◽  
Eunice Paisana ◽  
Tânia Carvalho ◽  
...  
Keyword(s):  
Brain Metastases ◽  
Anticancer Drugs ◽  
Cancer Progression ◽  
Metastatic Disease ◽  
Great Majority ◽  
Tumor Formation ◽  
Preclinical Studies ◽  
Primary Tumors ◽  
The Brain

ABSTRACTPurposeDissemination of cancer cells from primary tumors to the brain is observed in the great majority of cancer patients, contributing to increased morbidity and being the main cause of death. Most mechanistic and preclinical studies have relied on aggressive cancer cell lines, which fail to represent tumor heterogeneity and are unsuitable to validate therapies due to fast cancer progression in vivo.Experimental designWe established a unique library of subcutaneous and intracardiac patient-derived xenografts (PDXs) of brain metastases (BMs) from eight distinct primary tumor origins. Cancer progression in mice was compared to the matched patient clinical outcome, metastatic dissemination pattern and histopathological features. Preclinical studies with FDA approved drugs were performed.ResultsIn vivo tumor formation of flank-implanted BMs correlated with patients’ poor survival and serial passaging increased tumor aggressiveness. Subcutaneous xenografts originated spontaneous metastases in 61% of the cases, including in the leptomeningeal space (21%). The intracardiac model increased the tropism to the brain and leptomeninges (46%). Strikingly, 62% of intracardiac PDXs shared metastatic sites with the donor patients, including the primary cancer organ and the central nervous system (CNS). Of therapeutic relevance, PDX-derived cultures and corresponding mouse xenografts can be effectively treated with targeted anticancer drugs.ConclusionsPatient-derived models of BMs recapitulate the biology of human metastatic disease and can be a valuable translational platform for precision medicine.TRANSLATIONAL RELEVANCESubcutaneous and intracardiac mouse xenografts of human brain metastases exhibit a spontaneous dissemination pattern that resembles patients’ metastatic disease. The preclinical testing of targeted anticancer drugs using patient-derived cultures and patient-derived xenografts of brain metastasis showed an effective therapeutic response. These translational models represent an outstanding tool to advance the understanding of the biology of brain metastases and to foster the rapid discovery of novel therapeutics.

scholarly journals Decomposing the subclonal structure of tumors with two-way mixture models on copy number aberrations

2018 ◽  
Author(s):  
An-Shun Tai ◽  
Chien-Hua Peng ◽  
Shih-Chi Peng ◽  
Wen-Ping Hsieh
Keyword(s):  
Head And Neck Cancer ◽  
Head And Neck ◽  
Neck Cancer ◽  
Copy Number ◽  
Tumor Heterogeneity ◽  
Tumor Evolution ◽  
Depth Information ◽  
Sequencing Data ◽  
Single Nucleotide Variants ◽  
Copy Number Aberrations

AbstractMultistage tumorigenesis is a dynamic process characterized by the accumulation of mutations. Thus, a tumor mass is composed of genetically divergent cell subclones. With the advancement of next-generation sequencing (NGS), mathematical models have been recently developed to decompose tumor subclonal architecture from a collective genome sequencing data. Most of the methods focused on single-nucleotide variants (SNVs). However, somatic copy number aberrations (CNAs) also play critical roles in carcinogenesis. Therefore, further modeling subclonal CNAs composition would hold the promise to improve the analysis of tumor heterogeneity and cancer evolution. To address this issue, we developed a two-way mixture Poisson model, named CloneDeMix for the deconvolution of read-depth information. It can infer the subclonal copy number, mutational cellular prevalence (MCP), subclone composition, and the order in which mutations occurred in the evolutionary hierarchy. The performance of CloneDeMix was systematically assessed in simulations. As a result, the accuracy of CNA inference was nearly 93% and the MCP was also accurately restored. Furthermore, we also demonstrated its applicability using head and neck cancer samples from TCGA. Our results inform about the extent of subclonal CNA diversity, and a group of candidate genes that probably initiate lymph node metastasis during tumor evolution was also discovered. Most importantly, these driver genes are located at 11q13.3 which is highly susceptible to copy number change in head and neck cancer genomes. This study successfully estimates subclonal CNAs and exhibit the evolutionary relationships of mutation events. By doing so, we can track tumor heterogeneity and identify crucial mutations during evolution process. Hence, it facilitates not only understanding the cancer development but finding potential therapeutic targets. Briefly, this framework has implications for improved modeling of tumor evolution and the importance of inclusion of subclonal CNAs.

scholarly journals Genetic Alterations among Korean Melanoma Patients Showing Tumor Heterogeneity: A Comparison between Primary Tumors and Corresponding Metastatic Lesions

2018 ◽  
Vol 50 (4) ◽  
pp. 1378-1387 ◽  
Author(s):  
Si-Hyung Lee ◽  
Jee Eun Kim ◽  
Hong Sun Jang ◽  
Kyu Hyun Park ◽  
Byung Ho Oh ◽  
...  
Keyword(s):  
Tumor Heterogeneity ◽  
Genetic Alterations ◽  
Primary Tumors ◽  
Metastatic Lesions ◽  
Melanoma Patients

scholarly journals AKT1 is differentially expressed in primary tumors and brain metastases in humans with breast cancer.

2020 ◽  
Author(s):  
Shahan Mamoor
Keyword(s):  
Breast Cancer ◽  
Brain Metastases ◽  
Metastatic Breast ◽  
Metastatic Tumor ◽  
Clinical Problem ◽  
Central Nervous System Metastasis ◽  
Human Breast ◽  
Primary Tumors ◽  
Breast Tissues ◽  
The Brain

Metastasis to the brain is a clinical problem in patients with breast cancer (1-3). We mined published microarray data (4, 5) to compare primary and metastatic tumor transcriptomes to discover genes associated with brain metastasis in patients with metastatic breast cancer. We report here the differential expression of the protein kinase AKT1 in the primary tumors and brain metastases of humans with breast cancer. AKT1 mRNA was present at significantly increased quantities in brain metastatic tissues as compared to primary tumors of the breast. These data combined suggest that up-regulation of AKT1 is a conserved event, both during transformation of breast tissues and progression to central nervous system metastasis and further point to potential importance of AKT1 modulation during progression of human breast cancer.

scholarly journals Population Genetics Approaches to Quantify Clonal Evolution

Blood ◽  
2017 ◽  
Vol 130 (Suppl_1) ◽  
pp. SCI-37-SCI-37
Author(s):  
Christina Curtis
Keyword(s):  
Population Genetics ◽  
Tumor Growth ◽  
Tumor Heterogeneity ◽  
Big Bang ◽  
Colorectal Tumor ◽  
Neutral Evolution ◽  
Tumor Evolution ◽  
Big Bang Model ◽  
Tumor Types ◽  
The Big Bang

Abstract Cancer results from the acquisition of somatic alterations in an evolutionary process that typically occurs over many years, much of which is occult. Understanding the evolutionary dynamics that are operative at different stages of progression in individual tumors might inform the earlier detection, diagnosis, and treatment of cancer. For decades, tumor progression has been described as a gradual stepwise process, and it is through this lens that the underlying mechanisms have been interpreted and therapeutic strategies have been developed. Although these processes cannot be directly observed, the resultant spatiotemporal patterns of genetic variation amongst tumor cells encode their evolutionary histories. Cancer genome sequencing has thus yielded unprecedented insights into intra-tumor heterogeneity (ITH) and these data enable the inference of tumor dynamics using population genetics techniques. The application of such approaches suggests that tumor evolution is not necessarily gradual, but rather can be punctuated, resulting in revision of the de facto sequential clonal expansion model. For example, we previously described a Big Bang model of human colorectal tumor growth, wherein after transformation the neoplasm grows predominantly as a single terminal expansion in the absence of stringent selection, compatible with effectively neutral evolution1. In the Big Bang model, the timing of a mutation is the fundamental determinant of its frequency in the final tumor such that all major clones persist during growth and most detectable intra-tumor heterogeneity (ITH) occurs early. By analyzing multi-region and single gland genomic profiles in colorectal adenomas and carcinomas within a spatial agent-based tumor growth model and Bayesian statistical inference framework, we demonstrated the early origin of ITH and verified several other predictions of the Big Bang model. This new model provides a quantitative framework for understanding tumor progression with several clinical implications. In particular, rare but potentially aggressive subclones may be undetectable, providing a rich substrate for the emergence of resistance under treatment selective pressure. These data also suggest that some tumors may be born to be bad, wherein malignant potential is specified early. While not all tumors exhibit Big Bang dynamics, effectively neutral evolution has since been reported in other tumors and hence may be relatively common. These findings emphasize the need for methods to infer the role of selection in established human tumors and the systematic evaluation of distinct modes of evolution across tumor types and disease stages. To address this need, we developed an extensible population genetics framework to simulate spatial tumor growth and evaluate evidence for different evolutionary modes based on patterns of genetic variation derived from multi-region sequencing (MRS) data2. We demonstrate that while it is feasible to distinguish strong positive selection from neutral tumor evolution, weak selection and neutral evolution were indistinguishable in current data. Building on these findings, we developed a classifier that exploits novel measures of ITH and applied this to MRS data from diverse tumor types, revealing different evolutionary modes amongst treatment naïve tumors. To better understand evolutionary tempos during disease progression, we further characterized longitudinally sampled specimens. These findings have implications for forecasting tumor evolution and designing more effective treatment strategies. 1. Sottoriva A, Kang H, Ma Z, et al. A Big Bang model of human colorectal tumor growth. Nature Genetics. 2015;47:209-16. 2. Sun R, Hu Z, Sottoriva A, et al. Between-region genetic divergence reflects the mode and tempo of tumor evolution. Nature Genetics. 2017;49:1015-24. Disclosures No relevant conflicts of interest to declare.

scholarly journals FGF12 is differentially expressed in the brain metastases of patients with metastatic breast cancer.

2020 ◽  
Author(s):  
Shahan Mamoor
Keyword(s):  
Breast Cancer ◽  
Metastatic Breast Cancer ◽  
Brain Metastases ◽  
Metastatic Breast ◽  
Metastatic Tumor ◽  
Clinical Problem ◽  
Normal Breast ◽  
Primary Tumors ◽  
Breast Tissues ◽  
The Brain

Metastasis to the brain is a clinical problem in patients with breast cancer (1-3). We mined published microarray data (4, 5) to compare primary and metastatic tumor transcriptomes to discover genes associated with brain metastasis in patients with metastatic breast cancer. We found that the fibroblast growth factor 12, encoded by FGF12, was among the genes whose expression was most different in the brain metastases of patients with metastatic breast cancer as compared to normal breast tissues. FGF12 mRNA expression was significantly higher in brain metastatic tissues as compared to primary tumors of the breast. Up-regulation of FGF12 expression may contribute to metastasis of tumor cells from the breast to the brain in humans with metastatic breast cancer.

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