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Circulating Tumor Cell and Regulator T-Lymphocyte in Core Biopsy for Breast Cancer Panigoro, Sonar Soni; Kartini, Diani; Wulandari, Dewi; Supono, Arif
The New Ropanasuri Journal of Surgery
Publisher : UI Scholars Hub

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Abstract

Introduction: Breast cancer is the most common malignancy found in Indonesia. Core biopsy is one of the modalities used in breast cancer diagnosis with sensitivity of 91-99% and specificity of 96-100%. The procedure causes damage to tumor tissue thus causing tumor cells to enter circulation (CTC) and therefore acute inflammation and infiltration of inflammatory cells. In the final phase of infiltration, the number of Tregs cells will increase, as well as secretion of TGFβ and IL-10, creation of immunosuppresion microenvironment, COX2 stimulation by TGFβ then conversion of CD4+ T cells into FoxP3+ (Tregs), therefore the number of Tregs cells will increase. SOX-4 is activated by TGFβ, and then EMT proccess occurs, tumor cells enter circulation and CTC number will increase. Considering the side effect of core biopsy which is entrance of tumor cells to circulation causing the procedure to be in debate/contradicting opinions. Based on this premise, this study aims to investigate whether there is a change and relationship in Tregs count and CTC count before and after core biopsy procedure. Methods: This study includes 32 blood sample from patients with Stage III and IV breast cancer who went to surgical oncology outpatient clinic in Dr. Cipto Mangunkusumo National Central General Hospital (RSCM) and Gatot Subroto Army Hospital (RSPAD) before and 2 weeks after core biopsy during August to December 2016. Blood is sent to Clinical Pathology Laboratory of RSCM-FKUI to be measured its Tregs count (CD4, CD25, FoxP3 biomarker) and CTC count (CK19 biomarker) using flow cytometry. Statistical analysis was performed using Wilcoxon to determine the difference in CTC/Tregs count before and after core biopsy. Spearman correlation test was performed to determine the relationship between Tregs count and CTC count. Results: Results showed decrease in number of CTC after core biopsy with P value of 0.569 (p > 0.05). There was a decline in Tregs count after core biopsy with p value of 0.049. Small rho value (r=0.165, r=0.235, r=0.046) and p value greater than 0.05 signifies that there is no association between Tregs count to CTC count before or after procedure. Conclusion: Core biopsy do not cause increase in CTC or Tregs, however it cannot be concluded that the procedure is safe, despite the significant finding is only in the decline of Tregs count but not for CTC count. There is no association between Tregs count to CTC count before or after core biopsy.
SUPLEMEN: Registrasi Kanker Berbasis Rumah Sakit di Rumah Sakit Kanker "Dharmais" Pusat Kanker Nasional Pusat Kanker, 1993-2007 EVLINA SUZANNA; TIARLAN SIRAIT; PRADNYA SRI RAHAYU; GRACE SHALMONT; ELFIRA ANWAR; RIZKA ANDALUSIA; HARJATI -; SONAR SONI PANIGORO
Indonesian Journal of Cancer Vol 6, No 4 (2012): Oct - Dec 2012
Publisher : National Cancer Center - Dharmais Cancer Hospital

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33371/ijoc.v6i4.299

Abstract

http://indonesianjournalofcancer.org/2012/2012-no4-oct-dec/205-registrasi-kanker-berbasis-rumah-sakit-di-rumah-sakit-kanker-qdharmaisq-pusat-kanker-nasional-1993-2007?catid=95%3Asupplement
Total and Intratumoral CD8+ T Cell Expressions are Correlated with Miller Payne Grading and WHO Clinical Response of Neoadjuvant Chemotherapy Sonar Soni Panigoro; Sinta Chaira Maulanisa; Ahmad Kurnia; Denni Joko Purwanto; Primariadewi Rustamadji; Herqutanto Herqutanto; Ferry Sandra
The Indonesian Biomedical Journal Vol 15, No 2 (2023)
Publisher : The Prodia Education and Research Institute (PERI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18585/inabj.v15i2.2110

Abstract

BACKGROUND: Chemotherapy has reported to stimulate immune system through direct activation of cluster of differentiation (CD)8+ T cells. Neoadjuvant chemotherapy (NAC) is known to improve the clinical response of locally advanced breast cancer (LABC) patients. However, the immune response-related factor evaluation of NAC in LABC patients has not been routinely performed. Therefore, current study was conducted to evaluate the correlation of NAC-induced CD8+ T cell with chemotherapy response based on Miller Payne grading and World Health Organization (WHO) criteria.METHODS: LABC patients were recruited and data regarding age, gender, tumor, nodal stages, histopathological grade, estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and Ki67 were obtained. Biopsy and mastectomy tissues were collected and processed for hematoxylin-eosin and CD8 immunohistochemical staining. CD8+ T cell expression in peritumoral and intratumoral areas were documented and measured. Clinical responses based on Miller Payne grading and WHO were analyzed and correlated with CD8+ T cell expression.RESULTS: There were more subjects with high expression of total (80%), intratumoral (82.5%) and peritumoral (65%) CD8+ T cell expressions. The total (p=0.013) and intratumoral (p=0.015) CD8+ T cell expression, but not peritumoral CD8+ T cell expression, were significantly correlated with Miller Payne Grading. The total (p=0.009) and intratumoral (p=0.001) CD8+ T cell expressions were also significantly correlated with WHO clinical response.CONCLUSION: Total and intratumoral CD8+ T cell expressions are correlated with Miller Payne grading and WHO clinical response of NAC. Therefore, total and intratumoral CD8+ T cell expressions could be suggested as a predictive marker for clinical response of NAC.KEYWORDS: breast cancer, neoadjuvant chemotherapy, CD8, clinical response, Miller Payne, intratumoral, peritumoral 
Amino Acid Profile of Luminal A and B Subtypes Breast Cancer Sonar Soni Panigoro; Arif Kurniawan; Ramadhan Ramadhan; Ninik Sukartini; Herqutanto Herqutanto; Rafika Indah Paramita; Ferry Sandra
The Indonesian Biomedical Journal Vol 15, No 3 (2023)
Publisher : The Prodia Education and Research Institute (PERI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18585/inabj.v15i3.2109

Abstract

BACKGROUND: Amino acids are important for proliferation and maintenance of tumor cells. Breast cancer patients were found to have significant changes in the number of amino acids, which are assumed to be correlated with the molecular subtypes of breast cancer. Therefore, current study was conducted to analyze plasma amino acids in breast cancer patients with luminal A and B subtypes.METHODS: Breast cancer and control subjects were recruited, and venous blood was collected for the measurement of plasma amino acids. Total 19 plasma amino acids were measured using reverse-phase high-performance liquid chromatography with C18 column. Mean comparison for normally distributed and homogeneous data was further analzyed using independent sample T-test, with p<0.05 was considered as significant.RESULTS: From total 19 amino acids, only 7 amino acids; cysteine, glutamic acid, histidine, ornithine, threonine, tyrosine, valine, were statistically different between the healthy control and breast cancer subjects. Eventhough no amino acids was found to be statistically different between breast cancer subjects with luminal A and B subtypes, but some amino acids were found to be significantly different when correlated to various breast cancer risk factors.CONCLUSION: Amino acid profile of patients with Luminal A and B subtypes of breast cancer differs compared to healthy controls and is also correlated with breast cancer risk factors. Increase in cysteine level in Luminal A subtype patients and decrease of alanine and leucine in Luminal B subtype patients can be used as a biomarker.KEYWORDS: amino acid, plasma, breast cancer, risk factor, biomarker
Rencana Strategis Pengembangan Pusat Kanker Nasional Indonesia, Sebuah Studi Kasus Panigoro, Sonar Soni
Jurnal ARSI : Administrasi Rumah Sakit Indonesia Vol. 1, No. 1
Publisher : UI Scholars Hub

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Abstract

Cancer is a chronic disease and its prevalence is increasing nowadays. Uptudate, Indonesia doesn’t have a comprehensive program for National Cancer Control. This study aims to develop a strategic plan for the development of National Cancer Center for Indonesia. This study is conducted by using operational research approach, and is conducted during the months of March to December 2013 by involving various stakeholders. In Indonesia, cancer is the third killer disease among the NCD (Non Communicable Disease), the incidence is increasing as well as the funding for cancer treatment. All informants expressed the importance of establishing a national institute that plays a role in cancer control in a comprehensive manner. The most ideal institute is a non structural form and to achieve it, a National Cancer Center Development Team to be formed that coordinates with the Director of Cancer Hospital "Dharmais" which is a top referral center for cancer at this time. In conclusion, it is really important for national institute to take part in a comprehensive cancer control manner. The most ideal form of organization for the above function is a non-structural institution.
Impact of Artificial Intelligence on Mammography Interpretation by Breast Radiologists, Non-Breast Radiologists, and Senior Residents Darmiati, Sawitri; Afifi, Rahmi; Billy, Christy Amanda; Panigoro, Sonar Soni; Kartini, Diani; Prihartono, Joedo
Indonesian Journal of Cancer Vol 17, No 4 (2023): December
Publisher : http://dharmais.co.id/

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33371/ijoc.v17i4.1100

Abstract

Background: Artificial intelligence (AI) is recognized to have tremendous potential to revolutionize breast cancer management through mammography. However, the extent of its impact on radiologists with different levels of experience remains largely unexplored. Therefore, this study aimed to comprehensively show how AI could assist radiologists of varying expertise including breast and non-breast radiologists, as well as senior residents, in performing mammogram interpretation.Methods: This retrospective study analyzed eligible mammograms from Cipto Mangunkusumo Hospital between January 2017 and March 2021. Mammographic readings were conducted independently by two breast radiologists, two from other subspecialties, and three senior residents, all blinded to clinical information. AI standalone performance, as well as radiologists with and without AI assistance, was measured. Results: The results showed that a total of 886 eligible mammograms were analyzed. AI standalone performance, assessed using ROC curve analysis, yielded an AUC of 0.946 (95% CI, 0.925–0.967) with sensitivity and specificity of 90.1% and 93.6%, respectively. AI assistance significantly improved the sensitivity and specificity of all radiologists, regardless of experience level, with a median increase of 19.4% (IQR, 10.4–33.5%) and 12.1% (IQR, 5.2–16.2%), respectively. Moreover, there was a trend toward a higher increase with AI assistance in dense compared to fatty breasts.Conclusions: AI proved to be a highly effective diagnostic supplement for radiologists across varying experience levels, specifically in non-breast radiologists, offering the potential to add even greater value in cases of dense breast tissue. The results were derived from a national referral tertiary hospital that generally received many breast cancer cases referred from other hospitals for further treatment. Therefore, further studies incorporating different levels of hospitals were needed.
The Implementation of Machine Learning Algorithms for Breast Cancer Biomarker Validation in Metabolomics Studies Ratnaningayu, Nindhyana Diwaratri; Tedjo, Aryo; Sonar Soni Panigoro
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 25 No. 04 (2024): Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464)
Publisher : Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Negeri Padang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/eksakta/vol25-iss04/553

Abstract

Breast cancer is a heterogeneous disease characterized by distinct molecular and metabolic characteristics, making its diagnostics and treatment challenging. The existence of metabolic reprogramming in breast cancer underscores the potential to identify biomarkers through metabolomics studies, offering new avenues for personalized therapeutic approaches. Machine learning algorithms are now increasingly used to uncover complex patterns in metabolomics data. A comprehensive analysis of in silico metabolomics had successfully identified 24 significant metabolites after rigorous univariate and multivariate tests. Pathway analysis highlighted the apparent involvement of glycerolphosphate in glycerophospholipid and glycerolipid metabolism, indicating its potential role in breast cancer pathology. Validation of these 24 metabolites using machine learning algorithms provided superior results, with Neural Network achieving an AUC of 0.979 and a precision of 93%, Logistic Regression showing an AUC of 0.945 and a precision of 95.7%, as well as Random Forest reporting an AUC of 0.974 and a precision of 95.7% in predictive performance. These findings demonstrate the remarkable ability of machine learning to improve biomarker validation accuracy in metabolomics, facilitating better diagnostic strategies for breast cancer.
Relationship Between C-Reactive Protein-Albumin Ratio and Metastasis in Breast Cancer Hazmi, Mohammad Zul; Panigoro, Sonar Soni; Yulian, Erwin Danil; Nugroho, Nyityasmono Tri; Agustina, Amilya
Indonesian Journal of Cancer Vol 19, No 1 (2025): March
Publisher : http://dharmais.co.id/

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33371/ijoc.v19i1.1224

Abstract

Background: Breast cancer is a type of malignancy with the highest number of cases in the world and Indonesia. The C-reactive protein-albumin ratio (RCA) is a simple, feasible, and objective breast cancer serum marker representing inflammatory and nutritional status. There are not many studies regarding the relationship between RCA and breast cancer metastasis, especially in the advanced-stage case population in Indonesia.Method: Study with a cross-sectional design in 180 breast cancer patients stage III and IV at Cipto Mangunkusumo Hospital, who were diagnosed in 2018 until 2023. Comparative analysis of the RCA values between the groups with and without metastasis was carried out using the Chisquare test. All statistical test results are considered significant if the p-value is 0.05.Results: A receiver-operating characteristic curve (ROC) is a graphical analytical technique used to assess the effectiveness of a binary diagnostic classification method. The ROC area under the curve (AUC) value was 0.713 (IC 95%; 0.638–0.789) and significance 0.001, with the RCA cut-off value was 0.515 with sensitivity 74.4% and specificity 67.8%. The high RCA proportion was 53.3%. There is a significant relationship (p-value 0,001) between RCA level and the risk of metastasis in breast cancer patients. Liver and lung metastases of breast cancer are the most frequent locations. Conclusion: The CRP-albumin ratio has a significant relationship with the incidence of metastasis in breast cancer
Strategy for Diagnosing Breast Cancer in Indonesia during the COVID-19 Pandemic: Switching to Ultrasound-Guided Percutaneous Core Needle Biopsy Sobri, Farida Briani; Bachtiar, Adang; Panigoro, Sonar Soni; Rahmaania, Juwita Cresti; Yuswar, Patria Wardana; Krisnuhoni, Ening; Tandiari, Nelly
Kesmas Vol. 16, No. 3
Publisher : UI Scholars Hub

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Abstract

In this era of COVID-19, suspected breast cancer patients experience delay in diagnosis due to the fear of contracting the virus and reduction of non-COVID-19 health services. Furthermore, it may lead to potential increase in the incidence of advanced cancers in the future. Ultrasound-guided (US-guided) percutaneous core needle biopsy (CNB) is a great option for the diagnosis of cancer but it is poorly utilized. This study aimed to prove that the US-guided CNBis accurate when performed in a local setting and a potential solution for diagnosing breast cancer patients in this pandemic. In addition, it was a single health center cross-sectional study, and the participants were all breast cancer patients that had US-guided CNB from 2013-2019. The pathology results from US-guided CNB were compared to specimens from post-CNB surgeries. The data were collected from medical records and the immunohistochemistry (IHC) examinations were carried out for malignancy. There were 163 patients who were included in this study, 86 had malignancies and 77 had benign tumor reported in their CNB results. The US-guided CNB had 100% sensitivity and specificity compared to surgery. With its lower cost, time usage, and patient exposure to the hospital environment, US-guided CNB should replace open surgery biopsy for diagnosing suspicious breast cancers during the pandemic in Indonesia.
The Bioinformatics Application in Detecting Germline and Somatic Variants towards Breast Cancer using Next Generation Sequencing Retnomawarti, Rizka; Panigoro, Sonar Soni; Paramita, Rafika Indah
Journal of Applied Science, Engineering, Technology, and Education Vol. 5 No. 1 (2023)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.asci1608

Abstract

Breast cancer is the type of cancer with the most and the highest cases causing mortality in Indonesia, so an effective treatment is required to reduce the incidence and mortality rate due to cancer breasts. Most breast cancer patients are diagnosed at an advanced stage so the treatment used are limited and the risk of death becomes higher. Along with the development of human genome sequencing technology, the genetic examination of breast cancer is considered as an examination that can be used for early prevention and treatment management personally. Based on the target variants detected, the genetic examination of breast cancer can be divided into two, namely the examination of germline variants and somatic variants. Germline variant examination is intended to predict the risk of breast cancer which can be used as an early preventive measure, while somatic variant examination is intended for cancer diagnosis and management therapy. NGS technology is able to detect both types of variants in a number of genes associated with breast cancer in several samples effectively and quickly. However, the data generated from NGS technology is very large and complex, so the role of bioinformatics is required in analyzing and interpreting data. By utilizing bioinformatics pipelines and tools, analysis of germline variants and somatic variants in breast cancer can be carried out accurately so that the results of genetic examinations can be used as a step to treat breast cancer.