scholarly journals Early prediction of pathologic response to neoadjuvant treatment of breast cancer: use of a cell-loss metric based on serum thymidine kinase 1 and tumour volume

2020 ◽  
Author(s):  
Bernhard Tribukait
Keyword(s):  
Breast Cancer ◽  
Neoadjuvant Treatment ◽  
Tumour Response ◽  
Cell Loss ◽  
Tumour Volume ◽  
Tumour Cells ◽  
Early Prediction ◽  
Predictive Values ◽  
Cytotoxic Treatment ◽  
A Cell

Abstract Background: After neoadjuvant chemotherapy of breast cancer pathologic complete response (pCR) indicates a favorable prognosis. Among non-selected patients, pCR is, however, achieved in only 10-30%. Early evaluation of tumour response to treatment would facilitate individualized therapy, with ineffective chemotherapy interrupted or changed. The methodology for this purpose is still limited. Tumour imaging and analysis of macromolecules, released from disrupted tumour cells, are principal alternatives.Objective: To investigate whether a metric of cell-loss, defined as the ratio between serum concentration of thymidine kinase1 (sTK1, ng x ml-1) and tumour volume, can be used for early prediction of pathologic response.Methods: 104 women with localized breast cancer received neoadjuvant epirubicin/docetaxel in 6 cycles, supplemented with bevacizumab in cycles 3-6. The cell-loss metric was established at baseline (n=104), 48h after cycle 2 (n=104) and prior to cycle 2 (n=57). The performance of the metric was evaluated by association with pathologic tumour response at surgery 4 months later.Results: Treatment caused a rise in sTK1, a reduction in tumour volume and a marked increase in the cell-loss metric. Patients were subdivided into quartiles according to the baseline cell-loss metric. For these groups, baseline means were 0.0016, 0.0042, 0.0062, 0.0178 units. After subtraction of baselines, means for the quartiles 48h after treatment 2 were 0.002, 0.011, 0.030 and 0.357 units. pCR was achieved in 24/104, their distribution in the quartiles (11%, 11%, 23% and 46%) differed significantly (p=0.01). In 80 patients with remaining tumour, tumour size was inversely related to the metric (p=0.002). In 57 patients studied before treatment 2, positive and negative predictive values of the metric were 77.8% and 83.3%, compared to 40.5% and 88.7% 48h after treatment 2.Conclusion: A cell-loss metric, based on serum levels of TK1, released from disrupted tumour cells, and tumour volume, reveal tumour response early during neoadjuvant treatment. The metric reflect tumour properties that differ greatly between patients and determine the sensitivity to cytotoxic treatment. The findings point to the significance of cell loss for tumour growth rate. The metric should be considered in personalized oncology and in the evaluation of new therapeutic modalities.Trial registration: PROMIX (Clinical Trials.gov NCT000957125).https://clinicaltrials.gov/ct2/show/NCT00957125

scholarly journals Early prediction of pathologic response to neoadjuvant treatment of breast cancer: use of a cell-loss metric based on serum thymidine kinase 1 and tumour volume

2019 ◽  
Author(s):  
Bernhard Tribukait ◽  
Jonas Bergh ◽  
Thomas Hatschek
Keyword(s):  
Breast Cancer ◽  
Pathologic Complete Response ◽  
Neoadjuvant Treatment ◽  
Tumour Response ◽  
Cell Loss ◽  
Tumour Volume ◽  
Tumour Cells ◽  
Early Prediction ◽  
Cytotoxic Treatment ◽  
A Cell

Abstract Background After neoadjuvant chemotherapy of breast cancer pathologic complete response (pCR) indicates a favourable prognosis. Among non-selected patients, pCR is, however, achieved in only 10-30%. Early evaluation of tumour response to treatment would facilitate individualized therapy, with ineffective chemotherapy interrupted or changed. The methodology for this purpose is still limited. Tumour imaging and analysis of macromolecules, released from disrupted tumour cells are principle alternatives.Objective To investigate whether a metric of cell-loss, defined as the ratio between serum concentration of thymidine kinase1 (sTK1) (ng x ml -1 ) and tumour volume (cm 3 ), can be used in the early prediction of pathologic response.Methods 104 women with localized breast cancer received neoadjuvant epirubicin/docetaxel in 6 cycles, supplemented with bevacizumab in cycles 3-6. The cell-loss metric was established at baseline (n=104), prior to cycle 2 (n=57) and 48h after cycle 2 (n=104). The performance of the metric was evaluated by association with pathologic tumour response at surgery ̴ 16 weeks later.Results Means for the three points of the metric were 0.007, 0.084 and 0.107 units. For each individual, the baseline value was subtracted from the 48-h value and patients were grouped into quartiles. Means of these were: 0.002, 0.011, 0.030 and 0.357 units. The cell-loss metric was associated with the pCR in the quartiles: 11%, 11%, 23% and 46% (p=0.01). In the 80 patients with remaining tumour, pathologic tumour size was inversely related to the metric (p=0.002). In the subgroup of 57 patients, data obtained prior to the 2nd cycle indicated a higher predictive value than the data obtained 48h after this treatment.Conclusion A cell-loss metric, established by combining serum levels of TK1, released from disrupted tumour cells, and tumour volume, reveal tumour response early during neoadjuvant treatment. The metric appears to reflect a tumour property that differ greatly between patients and determines the sensitivity to cytotoxic treatment. The findings point to the significance of cell loss for the growth rate of tumours. The metric should be considered in personalized oncology and in the evaluation of new therapeutic modalities.

scholarly journals Early prediction of pathologic response to neoadjuvant treatment of breast cancer: use of a cell-loss metric based on serum thymidine kinase 1 and tumour volume

2020 ◽  
Author(s):  
Bernhard Tribukait
Keyword(s):  
Breast Cancer ◽  
Neoadjuvant Treatment ◽  
Tumour Response ◽  
Cell Loss ◽  
Tumour Volume ◽  
Pathologic Response ◽  
Tumour Cells ◽  
Early Prediction ◽  
Cytotoxic Treatment ◽  
A Cell

Abstract Background: After neoadjuvant chemotherapy of breast cancer pathologic complete response (pCR) indicates a favorable prognosis. Among non-selected patients, pCR is, however, achieved in only 10-30%. Early evaluation of tumour response to treatment would facilitate individualized therapy, with ineffective chemotherapy interrupted or changed. The methodology for this purpose is still limited. Tumour imaging and analysis of macromolecules, released from disrupted tumour cells, are principal alternatives. Objective: To investigate whether a metric of cell-loss, defined as the ratio between serum concentration of thymidine kinase1 (sTK1, ng x ml-1) and tumour volume, can be used for early prediction of pathologic response. Methods: 104 women with localized breast cancer received neoadjuvant epirubicin/docetaxel in 6 cycles, supplemented with bevacizumab in cycles 3-6. The cell-loss metric was established at baseline (n=104), 48h after cycle 2 (n=104) and prior to cycle 2 (n=57). The performance of the metric was evaluated by association with pathologic tumour response at surgery 4 months later. Results: Treatment caused a rise in sTK1, a reduction in tumour volume and a marked increase in the cell-loss metric. Patients were subdivided into quartiles according to the baseline cell-loss metric. For these groups, baseline means were 0.0016, 0.0042, 0.0062, 0.0178 units. After subtraction of baselines, means for the quartiles 48h after treatment 2 were 0.002, 0.011, 0.030 and 0.357 units. pCR was achieved in 24/104, their distribution in the quartiles (11%, 11%, 23% and 46%) differed significantly (p=0.01). In 80 patients with remaining tumour, tumour size was inversely related to the metric (p=0.002). In 57 patients studied before treatment 2, positive and negative predictive values of the metric were 77.8% and 83.3%, compared to 40.5% and 88.7% 48h after treatment 2. Conclusion: A cell-loss metric, based on serum levels of TK1, released from disrupted tumour cells, and tumour volume, reveal tumour response early during neoadjuvant treatment. The metric reflect tumour properties that differ greatly between patients and determine the sensitivity to cytotoxic treatment. The findings point to the significance of cell loss for tumour growth rate. The metric should be considered in personalized oncology and in the evaluation of new therapeutic modalities.

scholarly journals Early prediction of pathologic response to neoadjuvant treatment of breast cancer: use of a cell-loss metric based on serum thymidine kinase 1 and tumour volume

2020 ◽  
Author(s):  
Bernhard Tribukait ◽  
Jonas Bergh ◽  
Thomas Hatschek
Keyword(s):  
Breast Cancer ◽  
Neoadjuvant Treatment ◽  
Tumour Response ◽  
Cell Loss ◽  
Tumour Volume ◽  
Pathologic Response ◽  
Tumour Cells ◽  
Early Prediction ◽  
Cytotoxic Treatment ◽  
A Cell

Abstract Background: After neoadjuvant chemotherapy of breast cancer pathologic complete response (pCR) indicates a favourable prognosis. Among non-selected patients, pCR is, however, achieved in only 10-30%. Early evaluation of tumour response to treatment would facilitate individualized therapy, with ineffective chemotherapy interrupted or changed. The methodology for this purpose is still limited. Tumour imaging and analysis of macromolecules, released from disrupted tumour cells, are principal alternatives. Objective: To investigate whether a metric of cell-loss, defined as the ratio between serum concentration of thymidine kinase1 (sTK1, ng x ml-1) and tumour volume, can be used for early prediction of pathologic response. Methods: 104 women with localized breast cancer received neoadjuvant epirubicin/docetaxel in 6 cycles, supplemented with bevacizumab in cycles 3-6. The cell-loss metric was established at baseline (n=104), 48h after cycle 2 (n=104) and prior to cycle 2 (n=57). The performance of the metric was evaluated by association with pathologic tumour response at surgery 4 months̴ later.Results: Treatment caused a rise in sTK1, a reduction in tumour volume and a marked increase in the cell-loss metric. Patients were subdievided into quartiles according to the baseline cell-loss metric. For these groups, baseline means were 0.0016, 0.0042, 0.0062, 0.0178 units. After subtraction of baselines, means for the quartiles 48h after treatment 2 were 0.002, 0.011, 0.030 and 0.357 units. pCR was achieved in 24/104, their distribution in the quartiles (11%, 11%, 23% and 46% ) differed significantly (p=0.01).In 80 patients with remaining tumour, tumour size was inversely related to the metric (p=0.002). In 57 patients studied before treatment 2, positive and negative predictive values of the metric were 77.8% and 83.3%, compared to 40.5% and 88.7% 48h after treatment 2. Conclusion: A cell-loss metric, based on serum levels of TK1, released from disrupted tumour cells, and tumour volume, reveal tumour response early during neoadjuvant treatment. The metric reflect tumour properties that differ greatly between patients and determine the sensitivity to cytotoxic treatment. The findings point to the significance of cell loss for tumour growth rate. The metric should be considered in personalized oncology and in the evaluation of new therapeutic modalities.

scholarly journals Persistence of ctDNA in breast cancer patients during neoadjuvant treatment is a significant predictor of poor tumour response

2021 ◽  
pp. clincanres.3231.2021
Author(s):  
Qing Zhou ◽  
Simon P. Gampenrieder ◽  
Sophie Frantal ◽  
Gabriel Rinnerthaler ◽  
Christian F. Singer ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Neoadjuvant Treatment ◽  
Tumour Response ◽  
Breast Cancer Patients

Semi-quantitative gene expression profiling for therapy prediction in a breast cancer neoadjuvant therapy study applying docetaxel/epirubicin/cyclophosphamide

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 21144-21144
Author(s):  
U. Vogt ◽  
D. Kemming ◽  
B. Brandt ◽  
U. Bosse ◽  
U. Bonk ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Progression ◽  
Expression Profiling ◽  
Pearson Correlation ◽  
Neoadjuvant Treatment ◽  
Chemotherapy Resistance ◽  
Tumour Response ◽  
High Specificity ◽  
Cancer Genes ◽  
Breast Cancer Patients

21144 Background: More than 28000 curated human genes can be analyzed semi-quantitatively using a chemiluminescent detection technology and 60mer oligonucleotides on a Human Genome Survey Microarray (HGSM, Applied Biosytems). Methods: HGSM expression profiling was performed on biopsy samplesfrom a setting of patients under neoadjuvant treatment. The protocol for a phase II study was elaborated for the treatment of breast cancer patients suffering from a primary tumor > 1,5 cm or inflammatory breast cancer with Docetaxel / Epirubicin/Cyclophosphamide (TEC) prior to surgical treatment. The study was approved by the local ethical committee and 80 patients will be included into the study after written informed consent. 40 patients have been already included in the ongoing study. In this prospective study a biopsy from the tumor is taken before chemotherapy. Therefore, success of treatment is detectable directly at the operated residual tumor. Our results demonstrate a low rate of false-positives (1.2%), a high specificity and quantification accuracy of HGSM system. Comparison of data from HGSM and RT-PCR obtained on mRNA from fresh frozen tissue resulted a Pearson-correlation of 0.92 to 0.63 for the breast cancer genes. Results: Tumour response (pCR, pPR) of more than 70 % can be achieved using neoadjuvant TEC- regimen. 25 % of pCR in this study is comparable with data of other published neoadjuvant trails. First expression profiling results are obtainable showing that a subset of 148 genes indicates patients with complete remission (pCR, no detectable tumor at end of chemotherapy), partial remission (pPR) and progressive disease (pPD). Remarkable, that the expression profile clearly separated pCR and pPD tumors whereas pPR tumors presented with a closer relationship to pPD tumors than to pCR tumors but displayed small specific subprofiles. A comparable separation of the groups could not achieved by established tumor markers, e.g. ER, PgR, HER2, uPA etc. which are measured simultaneously on the HGSM. Conclusions: HGSM expression profiling is promising to have the potential to figure out genes that are related to cancer progression and chemotherapy resistance, especially in PST. No significant financial relationships to disclose.

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