scholarly journals Assessing tumor heterogeneity using ctDNA to predict and monitor therapeutic response in metastatic breast cancer

2019 ◽  
Vol 146 (5) ◽  
pp. 1359-1368 ◽  
Author(s):  
Fei Ma ◽  
Yanfang Guan ◽  
Zongbi Yi ◽  
Lianpeng Chang ◽  
Qiao Li ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Metastatic Breast Cancer ◽  
Tumor Heterogeneity ◽  
Therapeutic Response ◽  
Metastatic Breast

Assessing tumor heterogeneity using circulating tumor DNA to predict and monitor therapeutic response in metastatic breast cancer.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 11543-11543
Author(s):  
Fei Ma ◽  
Yanfang Guan ◽  
Zongbi Yi ◽  
Lianpeng Chang ◽  
Xuefeng Xia ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Metastatic Breast Cancer ◽  
Tumor Heterogeneity ◽  
Therapeutic Response ◽  
Metastatic Breast ◽  
Circulating Tumor Dna ◽  
Tumor Burden ◽  
Response To Treatment ◽  
Clonal Population ◽  
Tumor Dna

11543 Background: Within metastatic breast cancer (mBC), tumor heterogeneity limited efficacy and duration of response to treatment. In this study, circulating tumor DNA (ctDNA) was used to evaluate tumor heterogeneity as a prognostic factor and monitor therapeutic response in patients with mBC. Methods: We collected plasma samples from 37 HER2-positive mBC patients treated with pyrotinib. Target-capture deep sequencing was performed to detect somatic mutations in plasma ctDNA. Clonal population structures were identified based on variations from ctDNA using Bayesian cluster with PyClone. Molecular tumor burden index (mTBI) was calculated with the mean variant allele frequency of mutations in trunk clonal population. Results: Mutations in TP53 and genes of PI3K/Akt/mTOR pathway were associated with drug resistance for pyrotinib. The result showed that patients with resistant mutations occurring as a truncal event, who receiving monotherapy of pyrotinib, presented worse therapeutic effect (HR, 4.52; P = 0.03). The median PFS of patients with versus without resistant mutations in trunk clonal population was 7.8 weeks (95% CI 7.4 to 26.8 weeks) versus 31.6 weeks (95% CI 15.7 to 60 weeks), respectively. Patients with high heterogeneity (clonal population ≥3) had a significantly worse PFS (HR, 2.79; 95% CI 1.23 to 6.34; P = 0.014). The median PFS among patients with high versus low heterogeneity was 30.0 weeks (95% CI 13.9 to 53.5 weeks) versus 60.0 weeks (95% CI 31.4 to 84 weeks), respectively. Longitudinal monitoring of 21 patients during treatment showed positive correlation between mTBI in ctDNA and tumor size evaluated by CT imaging (P < 0.0001). Monitoring the mTBI in serial ctDNA increased sensitivity for prediction of progressive disease in 6 of 21 patients, with a mean time of 12.7 weeks earlier than using CT scan. ROC curve analysis showed an area under the curve value was 0.97 (p < 0.0001). Conclusions: Assessing tumor heterogeneity in ctDNA provides genetic predictors of treatment outcome. Molecular tumor burden in ctDNA is a potential indicator of therapeutic response. These observations might be supplements for the current therapeutic response evaluation.

scholarly journals Is There Any Rationale for Detecting Hormone Receptor/HER2 Status with Rebiopsy Without Progression Upfront Metastatic Breast Cancer? with 2 Cases

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Duman BB ◽  
Cil T
Keyword(s):  
Breast Cancer ◽  
Metastatic Breast Cancer ◽  
Maintenance Therapy ◽  
Hormone Receptor ◽  
Tumor Heterogeneity ◽  
Hormone Receptors ◽  
Triple Negative ◽  
Neoadjuvant Treatment ◽  
Metastatic Breast ◽  
Her2 Overexpression

Alteration of biomarkers is well-documented in breast cancer at locoregional recurrence or metastasis attributed to tumor heterogeneity and change in biology. There is some data about discordance between primary and metastatic sites. At the same time hormone, receptor status can change after neoadjuvant treatment and at the time of recurrence. Metastatic breast cancer without progression or recurrence after the targeted chemotherapy combination for planning maintenance therapy in Human epidermal growth factor receptor 2 (HER2) overexpression positive hormone receptors positive or triple-negative patient after chemotherapy. In guidelines, the time of rebiopsy has no exact time, if the time of biopsy is usually after the progression of the tumor. We presented cases in which we detected different hormone receptor statuses from the beginning without progression and before deciding on maintenance therapy. This subject is important for deciding therapy in the aspect of heterogeneous tumors like breast cancer. The important decision of rebiopsy time is debate. In this aspect, these two cases are important examples for these kinds of patients tumor heterogeneity in breast cancer is one of the most widely known entities. We found that two patients, one of whom was estrogen progesterone receptor negative HER2 3 (+++) at the time of diagnosis and the other who was triple negative at the time of diagnosis, had positive hormone receptors in the re-biopsies without progression. We aimed to discuss the tumor heterogeneity and timing of rebiopsy in breast cancer in the light of two cases.

scholarly journals A Digital RNA Signature of Circulating Tumor Cells Predicting Early Therapeutic Response in Localized and Metastatic Breast Cancer

2018 ◽  
Vol 8 (10) ◽  
pp. 1286-1299 ◽  
Author(s):  
Tanya T. Kwan ◽  
Aditya Bardia ◽  
Laura M. Spring ◽  
Anita Giobbie-Hurder ◽  
Mark Kalinich ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Metastatic Breast Cancer ◽  
Tumor Cells ◽  
Circulating Tumor Cells ◽  
Therapeutic Response ◽  
Metastatic Breast ◽  
Rna Signature

Efficacy of Lower Dose Capecitabine in Patients with Metastatic Breast Cancer and Factors Influencing Therapeutic Response and Outcome

2007 ◽  
Vol 100 (1) ◽  
pp. 27-32 ◽  
Author(s):  
Canfeza Sezgin ◽  
Ender Kurt ◽  
Turkan Evrensel ◽  
Necmettin Ozdemir ◽  
Osman Manavoglu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Metastatic Breast Cancer ◽  
Therapeutic Response ◽  
Metastatic Breast ◽  
Factors Influencing

scholarly journals Quantitative Evaluation of Therapeutic Response by FDG-PET–CT in Metastatic Breast Cancer

2016 ◽  
Vol 3 ◽  
Author(s):  
Dorothée Goulon ◽  
Hatem Necib ◽  
Brice Henaff ◽  
Caroline Rousseau ◽  
Thomas Carlier ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Metastatic Breast Cancer ◽  
Quantitative Evaluation ◽  
Fdg Pet ◽  
Therapeutic Response ◽  
Metastatic Breast ◽  
Pet Ct ◽  
Fdg Pet Ct

scholarly journals Transcriptome analysis of heterogeneity in mouse model of metastatic breast cancer

2021 ◽  
Vol 23 (1) ◽  
Author(s):  
Anastasia A. Ionkina ◽  
Gabriela Balderrama-Gutierrez ◽  
Krystian J. Ibanez ◽  
Steve Huy D. Phan ◽  
Angelique N. Cortez ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Metastatic Breast Cancer ◽  
Mouse Model ◽  
Cancer Cells ◽  
Transcriptome Analysis ◽  
Tumor Heterogeneity ◽  
Cancer Metastasis ◽  
Metastatic Breast ◽  
Organ Tropism

Abstract Background Cancer metastasis is a complex process involving the spread of malignant cells from a primary tumor to distal organs. Understanding this cascade at a mechanistic level could provide critical new insights into the disease and potentially reveal new avenues for treatment. Transcriptome profiling of spontaneous cancer models is an attractive method to examine the dynamic changes accompanying tumor cell spread. However, such studies are complicated by the underlying heterogeneity of the cell types involved. The purpose of this study was to examine the transcriptomes of metastatic breast cancer cells using the well-established MMTV-PyMT mouse model. Methods Organ-derived metastatic cell lines were harvested from 10 female MMTV-PyMT mice. Cancer cells were isolated and sorted based on the expression of CD44low/EpCAMhigh or CD44high/EpCAMhigh surface markers. RNA from each cell line was extracted and sequenced using the NextSeq 500 Illumina platform. Tissue-specific genes were compared across the different metastatic and primary tumor samples. Reads were mapped to the mouse genome using STAR, and gene expression was quantified using RSEM. Single-cell RNA-seq (scRNA-seq) was performed on select samples using the ddSeq platform by BioRad and analyzed using Seurat v3.2.3. Monocle2 was used to infer pseudo-time progression. Results Comparison of RNA sequencing data across all cell populations produced distinct gene clusters. Differential gene expression patterns related to CD44 expression, organ tropism, and immunomodulatory signatures were observed. scRNA-seq identified expression profiles based on tissue-dependent niches and clonal heterogeneity. These cohorts of data were narrowed down to identify subsets of genes with high expression and known metastatic propensity. Dot plot analyses further revealed clusters expressing cancer stem cell and cancer dormancy markers. Changes in relevant genes were investigated across pseudo-time and tissue origin using Monocle2. These data revealed transcriptomes that may contribute to sub-clonal evolution and treatment evasion during cancer progression. Conclusions We performed a comprehensive transcriptome analysis of tumor heterogeneity and organ tropism during breast cancer metastasis. These data add to our understanding of metastatic progression and highlight targets for breast cancer treatment. These markers could also be used to image the impact of tumor heterogeneity on metastases.

Analysis of circulating tumor DNA to monitor metastatic breast cancer patients treated with first-line chemotherapy (CAMELLIA study).

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e14568-e14568
Author(s):  
Zongbi Yi ◽  
Fei Ma ◽  
Guohua Rong ◽  
Jin Li ◽  
Lianpeng Chang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Metastatic Breast Cancer ◽  
Therapeutic Response ◽  
Metastatic Breast ◽  
Circulating Tumor Dna ◽  
Tumor Burden ◽  
Breast Cancer Patients ◽  
First Line ◽  
Tumor Dna ◽  
Line Chemotherapy

e14568 Background: Our precious study indicated that the dynamic changes in circulating tumor DNA (ctDNA) could reflect changes in tumor burden. We conduct this study to validate the role of ctDNA as a therapeutic response biomarker in a larger cohort prospective phase III randomized multicenter study. Methods: In this study, we collected 292 serial ctDNA samples from 125 metastatic breast cancer patients treated with first line chemotherapy. Target-capture deep sequencing of 1021 genes was performed to detect somatic variants in ctDNA. Results: 81.4% patients had detectable ctDNA at baseline. An undetectable ctDNA at baseline was associated with a lower disease volume (p < 0.05). The commonly mutated genes were PIK3CA (35.0%), TP53 (34.2%), MLL3 (9.4%) and ESR1 (9.4%). Kaplan–Meier analysis showed that TP53 gene mutations and remaining C2 (detected at base line and remaining at the second cycle of chemotherapy) were significantly associated with poor PFS. Longitudinal monitoring of 27 patients during treatment showed that the molecular tumor burden index ([mTBI] a measure of the percentage of ctDNA in samples) was positively correlated with tumor size as evaluated by computed tomography (P < 0.05). The evaluations based on mTBI values were consistent with those based on CT scans in 87.5% of cases at the endpoint of clinical observation. Conclusions: ctDNA could be used to predict treatment outcomes and the mTBI is a potential method to assess therapeutic response in metastatic breast cancer. Clinical trial information: NCT01917279.

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