The actual scenario of neoadjuvant chemotherapy of breast cancer in developing country: a report of 80 cases of breast cancer from a tertiary cancer center in India

Identification of tumor biomarkers for pathological complete response to neoadjuvant treatment in locally advanced breast cancer

BACKGROUND

Therapeutic response predictors like age, nodal status, and tumor grade and markers, like ER/PR, HER2, and Ki67, are not reliable in predicting the response to a specific form of chemotherapy. The current study aims to identify and validate reliable markers that can predict pathological complete response (pCR) in fluorouracil, epirubicin, and cyclophosphamide (FEC)-based neoadjuvant therapy with (NACT/RT) and without concurrent radiation (NACT).

MATERIALS AND METHODS

Tandem mass tag (TMT) quantitative liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to identify differentially expressed proteins from core needle breast biopsy between pCR (n = 4) and no-pCR (n = 4). Immunoblotting of shortlisted proteins with the tissue lysates confirmed the differential expression of the markers. Further, immunohistochemistry (IHC) was performed on formalin-fixed paraffin-embedded sections of treatment-naive core needle biopsies. In the NACT, 29 pCR and 130 no-pCR and in NACT/RT, 32 pCR and 71 no-pCR were used.

RESULTS

733 and 807 proteins were identified in NACT and NACT/RT groups, respectively. Ten proteins were shortlisted for validation as potential pCR-predictive markers. THBS1, TNC, and DCN were significantly overexpressed in no-pCR in both the groups. In NACT, CPA3 was significantly upregulated in the no-pCR. In NACT/RT, HnRNPAB was significantly upregulated and HMGB1 significantly downregulated in the no-pCR. HMGB1 was the only marker to show prognostic significance.

CONCLUSION

Quantitative proteomics followed by IHC identified and validated potential biomarkers for predicting patient response to therapy. These markers can be used, following larger-scale validation, in combination with routine histological analysis providing vital indications of treatment response.

Dual-Branch Convolutional Neural Network Based on Ultrasound Imaging in the Early Prediction of Neoadjuvant Chemotherapy Response in Patients With Locally Advanced Breast Cancer

The early prediction of a patient's response to neoadjuvant chemotherapy (NAC) in breast cancer treatment is crucial for guiding therapy decisions. We aimed to develop a novel approach, named the dual-branch convolutional neural network (DBNN), based on deep learning that uses ultrasound (US) images for the early prediction of NAC response in patients with locally advanced breast cancer (LABC). This retrospective study included 114 women who were monitored with US during pretreatment (NAC pre) and after one cycle of NAC (NAC1). Pathologic complete response (pCR) was defined as no residual invasive carcinoma in the breast. For predicting pCR, the data were randomly split into a training set and test set (4:1). DBNN with US images was proposed to predict pCR early in breast cancer patients who received NAC. The connection between pretreatment data and data obtained after the first cycle of NAC was considered through the feature sharing of different branches. Moreover, the importance of data in various stages was emphasized by changing the weight of the two paths to classify those with pCR. The optimal model architecture of DBNN was determined by two ablation experiments. The diagnostic performance of DBNN for predicting pCR was compared with that of four methods from the latest research. To further validate the potential of DBNN in the early prediction of NAC response, the data from NAC pre and NAC1 were separately assessed. In the prediction of pCR, the highest diagnostic performance was obtained when combining the US image information of NAC pre and NAC1 (area under the receiver operating characteristic curve (AUC): 0.939; 95% confidence interval (CI): 0.907, 0.972; F1-score: 0.850; overall accuracy: 87.5%; sensitivity: 90.67%; and specificity: 85.67%), and the diagnostic performance with the combined data was superior to the performance when only NAC pre (AUC: 0.730; 95% CI: 0.657, 0.802; F1-score: 0.675; sensitivity: 76.00%; and specificity: 68.38%) or NAC1 (AUC: 0.739; 95% CI: 0.664, 0.813; F1-score: 0.611; sensitivity: 53.33%; and specificity: 86.32%) (p<0.01) was used. As a noninvasive prediction tool, DBNN can achieve outstanding results in the early prediction of NAC response in patients with LABC when combining the US data of NAC pre and NAC1.

Late Effects of Breast Cancer Treatment and Outcome after Corrective Interventions

Purpose:

To study the late toxicities of treatment and its impact on Breast cancer survivors among Indian patients.

Materials and Methods:

Our study recruited 152 curatively treated non metastatic carcinoma breast patients. The baseline demographic details, disease related and treatment related information were collected. The late effects included breast cancer related lymphedema, shoulder dysfunction, treatment induced bone loss, hypothyroidism, cardiac dysfunction, and chemotherapy induced cognitive dysfunction and Quality of life.

Results:

The median age was 47 years (range 27 -72 years). The cumulative frequency of BCRL and shoulder dysfunction was 31.57% and 34.86% respectively. The improvement in BCRL with corrective intervention was not statistically significant. The BCRL was significantly associated with shoulder dysfunction. The frequency of loss of bone mineral density was 38.15%. There was statistically significant improvement in bone mineral density with interventions. The cumulative rate of hypothyroidism and cardiac dysfunction was 14.47 % and 2.17% respectively which improved after corrective therapy. We did not find any delayed cognitive dysfunction. There was improvement in global health, physical function, role function, fatigue, Nausea, vomiting, pain scores, insomnia, Loss of appetite, diarrhea and arm symptoms over time with intervention.

Conclusion:

Our study has shown that nearly half of the survivors were suffering from at least one of the late effects. The intervention helped in improving the loss of bone mineral density, hypothyroidism, cardiac dysfunction and quality of life in Breast cancer survivors.

Modulation of SOX2 expression delineates an end-point for paclitaxel-effectiveness in breast cancer stem cells

Tumor relapse in triple negative breast cancer patients has been implicated to chemoresistant cancer stem cells (CSCs), which under favorable conditions culminate in tumor re-formation and metastasis. Hence, eradication of CSCs during systemic chemotherapy is imperative. CSCs were sorted using immuno-phenotyping and aldefluor assay. Gene expression profiling of normal breast stem cells and breast CSCs from chemo-treated patients were carried out. Silencing SOX2 was achieved by siRNA method. Mammosphere culture and wound healing assays were carried out to assess efficacy of CSCs. Microarray analysis revealed elevated expression of SOX2, ABCG2 and TWIST1, unraveling an intertwined pluripotency-chemoresistance-EMT axis. Although paclitaxel treatment led to temporary arrest of cell migration, invasiveness resumed after drug removal. The ‘twist in the tale’ was a consistently elevated expression of TWIST1, substantiating that TWIST1 can also promote stemness and chemoresistance in tumors; hence, its eradication was imperative. Silencing SOX2 increased chemo-sensitivity and diminished sphere formation, and led to TWIST1 down regulation. This study eventually established that SOX2 silencing of CSCs along with paclitaxel treatment reduced SOX2-ABCG2-TWIST1 expression, disrupted sphere forming capacity and also reduced invasiveness by retaining epithelial-like properties of the cells, thereby suggesting a more comprehensive therapy for TNBC patients in future.

A Prospective Comparative Study of the Toxicity Profile of 5-Flurouracil, Adriamycin, Cyclophosphamide Regime VS Adriamycin, Paclitaxel Regime in Patients with Locally Advanced Breast Carcinoma

INTRODUCTION

A 5-flurouracil, Adriamycin, Cyclophosphamide (FAC) and Adriamycin, Paclitaxel (AT) are two popular chemotherapeutic regimens for treatment of breast carcinoma. The most time tested and popular regimen is FAC. It is extensively studied for efficacy and toxicity. But data regarding toxicity profile and efficacy of AT regimen is sparse.

AIM

To study the toxicity profile, severity of toxicities and clinical response rate of FAC and AT regimens in patients with locally advanced breast carcinoma.

MATERIALS AND METHODS

A prospective observational study with 50 patients in each treatment arm. Study duration was 12 months from November 2012 to October 2013. Consecutive patients with locally advanced breast carcinoma receiving treatment with either FAC or AT regimen, satisfying inclusion criteria were enrolled into the study after getting informed written consent. Prior to initiation of treatment detailed medical history was taken from all patients. General clinical examination, examination of organ systems and local examination of breast lump were done. After each cycle of chemotherapy and after completion of treatment patients were interviewed and examined for clinical response and toxicities. Toxicities were graded with WHO toxicity grading criteria. All data were entered in a structured proforma. At least 50% reduction in tumour size was taken as adequate clinical response.

STATISTICAL ANALYSIS

Data was analysed using Chi-square test with help of Excel 2007 and SPSS-16 statistical software.

RESULTS

Different pattern of toxicities were seen with FAC and AT regimens. Anaemia, thrombocytopenia, stomatitis, hyperpigmentation, photosensitivity and diarrhoea were more common with patients receiving FAC regimen. Leucopenia, peripheral neuropathy, myalgia, arthralgia, vomiting and injection site reactions were more common in AT regimen. Both FAC and AT regimens gave 100% clinical response.

CONCLUSION

FAC and AT regimens are equally efficacious but have different toxicity profiles. Patient's predisposition to toxicities may govern the selection of a particular regime.