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  Table of Contents  
Year : 2021  |  Volume : 58  |  Issue : 4  |  Page : 598-602

NGS-based profiling of key cancer genes in Indian triple-negative breast cancer patients reinforces molecular heterogeneity of the disease

1 PierianDx India Pvt. Ltd. Pune, Maharashtra, India
2 St. John's Research Institute, Bengaluru, Karnataka, India
3 Prashanti Cancer Care Mission (PCCM); Center for Translational Cancer Research - a joint initiative of PCCM and Indian Institute of Science Education and Research (IISER), Pune, Maharashtra, India
4 Prashanti Cancer Care Mission (PCCM), Pune, Maharashtra, India

Date of Submission01-May-2020
Date of Decision10-May-2020
Date of Acceptance22-Oct-2020
Date of Web Publication14-Sep-2021

Correspondence Address:
Nandini A Sahasrabuddhe
PierianDx India Pvt. Ltd. Pune, Maharashtra
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/ijc.IJC_432_20

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 » Abstract 

Triple-negative breast cancers (TNBC) are one of the most aggressive forms of breast cancers. With poor patient outcomes, it presents a great burden on the healthcare systems. There have been some efforts to explore the genomic changes that occur in TNBCs. However, there is not enough data on Indian TNBCs. We sought to understand the mutational landscape of key cancer-associated genes in Indian TNBC patients using TruSeq Cancer Amplicon Panel. We sequenced 51 TNBC patient samples and found great heterogeneity amongst samples with respect to the genomic variants. Several previously reported including alterations in PI3K-AKT pathway genes were also identified. Likewise, we identified several novel high-frequency variants, for example, GNAQ F341S (17%), the functional role of which remains unclear. Our study lays the foundation of larger efforts needed to understand the genomic landscape of Indian TNBCs which can aid in classification and better therapeutic management of patients.

Keywords: Mutation, next-generation sequencing, precision medicine, triple-negative breast cancer

How to cite this article:
Sahasrabuddhe NA, Korlimarla A, Kulkarni M, Kusuma V, Prabhu JS, Dixit S, Deshmukh C, Sridhar T S, Phatak A, Koppiker C. NGS-based profiling of key cancer genes in Indian triple-negative breast cancer patients reinforces molecular heterogeneity of the disease. Indian J Cancer 2021;58:598-602

How to cite this URL:
Sahasrabuddhe NA, Korlimarla A, Kulkarni M, Kusuma V, Prabhu JS, Dixit S, Deshmukh C, Sridhar T S, Phatak A, Koppiker C. NGS-based profiling of key cancer genes in Indian triple-negative breast cancer patients reinforces molecular heterogeneity of the disease. Indian J Cancer [serial online] 2021 [cited 2022 Dec 3];58:598-602. Available from:

 » Introduction Top

Triple-negative breast cancers (TNBC) are characterized by the very low or absence of hormone receptor expression and lack of HER2 amplification. TNBCs are characterized by an aggressive clinical course and poor prognosis compared to other subtypes. This aggressive subtype is highly prevalent among Indian women and occurs in about 20–30% of all patients with breast cancer.[1],[2] While there are targeted therapies available for hormone receptor-positive and HER2 amplified subtypes; no targeted therapies are yet approved for TNBCs. Though, patients are reported to respond to chemotherapies, most of the cases eventually progress and metastasize. Molecular heterogeneity of TNBCs is reported in several earlier studies.[3] To date, many studies mainly focused on mRNA expression and DNA copy numbers.[4],[5] Some studies have investigated genomic alterations in TNBCs in specific ethnic or racial groups. While there is consensus in some genomic features such as the high TP53 mutation rate across these studies, there are some observed variations. Basal-like and triple-negative breast cancers show a high frequency of somatic mutations in tumor suppressor protein TP53 (80%), followed by PIK3CA. Bailey et al. have done the most recent compressive analysis of the cancer genome  Atlas More Details (TCGA) datasets for finding driver somatic mutations.[6] The study has uncovered up-to 6% frequency of ARID1A which is involved in chromatin re-modeling and is known to facilitate KRAS signaling. KRAS was also found to be mutated in the same study in breast cancers. These driver mutations were earlier identified to be associated with other cancers, are now uncovered as lower frequency driver mutations in breast cancer. A recent study carried out by Jiang et al. highlights the differences between TNBCs in Chinese and African-Americans and/or Caucasians. The study reported that Chinese TNBCs show a higher percentage of copy number gains in chromosome 22 and a higher mutation rate of PIK3CA compared to TNBCs in Caucasians and/or African-Americans from the TCGA study.[7] These data warrant investigation of the genomic landscape to understand the commonalities as well as unique features of Indian TNBCs.

 » Case History Top

We employed next-generation sequencing (NGS)-based TruSeq Amplicon—Cancer Panel (Illumina Inc., USA) (TSACP) for investigating genomic alterations in key cancer genes. TSACP targets 48 genes with 212 amplicons and covers several mutational hotspots in those genes. With an NGS-based panel, it was possible to achieve a high depth of sequence coverage which is essential considering the heterogeneous nature of TNBCs.

We characterize the genomic alterations of TNBC from over 50 Indian patients from a multicentric case series. Patient recruitment was multicentric. Institutional ethics committee approval was obtained from respective recruiting centers and informed consent was obtained from all participating patients. Formalin-fixed, paraffin-embedded (FFPE) tumor blocks were stained with hematoxylin and eosin, and a board-certified pathologist evaluated tumor percentage. The tumor blocks with more than 50% tumor content were selected and sectioned into 10 μ ribbons. Every step in the workflow was followed according to the manufacturer's instructions. Briefly, genomic DNA was extracted from 10 μ sections obtained from FFPE block using QIAamp DNA FFPE Tissue Kit (Qiagen, Germany). Quantitation and quality check (QC) of extracted DNA were carried out using Qubit (Invitrogen, USA). After QC of libraries, samples were loaded and run on MiSeq V2 150x2. Along with samples, Tru-Q 4 (5% Tier) Reference Standard (Horizon Discovery, USA) were loaded as replicates for every TSACP NGS analysis. Tru-Q 4 control was selected to suit a range of expected allele frequency and type of mutations. Consistency across and intra-runs was assessed for data reproducibility. Variants identified in the target region of the Tru-Q 4 control samples were found to be 100% reproducible. Based on this analysis, bioinformatics analysis parameters for samples were fixed. The mean coverage cut-off was set to 800× to select samples for further analysis. Single-nucleotide polymorphisms above 5% and indels above 10% variant allele fraction were considered for analysis.

Clinical Genomics Workspace (PierianDx, USA) was used to identify and classify variants in 5 levels: 1) Pathogenic in patient's tumor type, 2) Pathogenic in other tumor types, 3) Variants reported in cancer, 4) Variants of unknown significance, 5) Polymorphisms. For further analysis, polymorphisms were not considered. Literature and bioinformatics analysis was carried out to understand the clinical relevance of identified variants.

One hundred and sixteen patients from an Indian cohort who were diagnosed with primary TNBC were included in the study and their tumor FFPE block collected. All 116 were women. Out of 116 tissue samples, 80 passed the QC test for DNA quality, 51 samples showed minimum 800x coverage in NGS were included in the somatic mutation profiling study [Figure 1].
Figure 1: Flowchart depicting sample pipeline for somatic mutation study; FFPE: Formalin-fixed paraffin-embedded; QC: Quality check; NGS: Next-generation sequencing

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Clinical details of the patient group have been represented in [Table 1]. The average age and standard deviation (SD) of 51 patients at diagnosis was 52.47 ± 14 years. The majority of the patients (70%) were categorized as early-stage breast cancer (stage I and stage IIa/b). Over 65% showed high-grade tumors (grade III). About 94% of the patients were 1-3 lymph nodes positive (N1). Fifteen patients had a follow-up period of an average of 3 years (and a median of 2.7 years). There were six patients with clinical relapses within the first 3-years of follow-up; four cases were in stage IIa and two cases were in stage I. Five patients died during the follow-up period due to cancer-associated causes.
Table 1: Demographic table with distribution of clinical characteristics of patients

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TSACP panel-based analysis of 51 TNBC samples identified 2,102 non-synonymous alterations of which majority i.e. 2,041 were substitutions. Insertions/deletions/indels accounted for 62 alterations, most of which are deemed to result in frameshift events. All non-synonymous mutations identified in the study are listed in [Table S1] (available online only) [Additional file 1]. [Figure 2] depicts the heatmap of the frequency of unique gene mutations observed in assessed TNBC samples. A wide variety of mutations was observed across the samples corroborating the previously reported mutational heterogeneity of TNBCs. Several of the frequently mutated genes identified in our study such as TP53, ERBB4, APC, and PTEN have been previously reported in TNBCs supporting our data. At least one alteration in TP53 was found in 76% of the samples. Activating mutations in PIK3CA were found in ~5% of the patients. The mutation frequency observed in these key genes appears to be similar between Indian TNBCs and the frequency reported by the TCGA.[8] Many hotspots were identified in TP53 that have been previously reported to have clinical significance. Similarly, inactivating mutations of PTEN and activating mutations such as H1047R and E454K were identified in PIK3CA. Such representative clinically relevant mutations are depicted in [Figure 3]a. Several mutations were observed in multiple patients, for which the clinical significance in TNBCs is not investigated completely. Representative high-frequency mutations observed in the study are shown in [Figure 3]b. GNAQ was observed to be mutated in multiple TNBC patients. Though it has been reported to be mutated in TNBCs previously, the clinical significance of GNAQ mutations in TNBCs remains unclear.[9] Previous studies have reported that FBXW7 mutations are more common in estrogen receptor (ER+) breast cancers. However, we identified several patient samples that harbored one or more mutations in FBXW7.[10],[11],[12]
Figure 2: Heatmap representation of mutational data for the 51 triple-negative breast cancer (TNBC) samples

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Figure 3: (a) Representative clinically relevant mutations identified in Indian triple-negative breast cancers (TNBCs). (b) Representative high-frequency mutations identified in Indian TNBCs

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Several clinically important mutations reported in other cancers were also identified in the Indian TNBC patients. PTPN11(SHP2) A72V is reported in several cancers including lung and hematological cancers. It is known to elevate the phosphate activity of SHP2.[13] Activation of SHP2 has been linked to several oncogenic processes in breast cancers including TNBCs.[14],[15] V722I, a known gain-of-function mutation in the pseudokinase domain of JAK3 was identified in some patients. It is reported to disrupt the autoregulation of JAK3 and transform Ba/F3 cells.[16],[17] We also identified variants at a low frequency which are known rare activating EGFR mutations such as G719C and T725M.[18] The clinical significance of such mutations in TNBCs warrants further investigation.

Out of 51 patients, follow-up information was available for 15 patients. In such a small sample set, associations observed between clinical outcomes and mutation frequencies were not of any significance.

From a targeted therapy perspective, there have been preclinical studies on the reactivation of TP53. However, that remains to be validated in the clinical setting. Alpelisib is recently approved by the Food and Drugs Administration (FDA) for hormone receptor-positive metastatic breast cancer harboring PIK3CA hotspots. However, it is not yet approved for TNBCs. Inhibition of the PI3K pathway does present as a possible future line of therapy for a subgroup of TNBC patients. Some patients in the study show mutated genes associated with homologous recombination defect (HRD). In conjunction, HRD testing of these patients will be helpful to determine the course of treatment.

 » Discussion Top

In summary, our data demonstrate the mutational heterogeneity observed in Indian TNBC patients. For some of the previously reported key mutated genes in TNBCs such as TP53 and PIK3CA, GNAQ, we observe similar gene mutations in the Indian TNBCs. It has been demonstrated that the presence of PIK3CA mutations confers luminal-like properties to the tumors and showed response to PI3K/AKT/mTOR inhibitors making it clinically significant and an important event in TNBC pathogenesis.[19] TP53 mutations are associated with overall poor prognosis, and groups around the world are exploring what optimal novel therapies can be therapeutically leveraged for these events. GNAQ encodes a G-class seven-transmembrane domain receptor that activates phospholipase C-Beta and has downstream effects on the RAS signaling pathway and upstream effect in the calcium signaling pathway.[20] By computational analysis of vast cancer genomics databases, the Cancer Genome Atlas and Molecular Taxonomy of Breast Cancer International Consortium (TCGA and METABRIC), we obtained evidence that activating mutations in GNAQ are implicated as important biomarkers in melanomas and gastric cancer and more recently in TNBC. Additionally, we identify some known gain-of-function mutations which need to be further investigated from the therapeutic perspective. Considering the small patient number considered in the study, statistically significant clinicopathological correlation with mutations was not observed. We demonstrate the feasibility of NGS platforms to stratify Indian TNBC patients based on their molecular profile for the better assisted clinical decision, in spite of a significant fall out of samples due to QC. NGS is rapidly becoming adopted for clinical diagnosis predominantly in oncology. Archival tissue represents a valuable resource but also comes with challenges for analysis due to quality, fixation conditions, DNA-protein cross-linking, and inhibitors that come with fixation procedures. In India, these factors are mostly out of control of investigators but with standardization of pre-analytical procedures failure of DNA QC can be significantly reduced. Data from a comparative analysis of DNA as well as libraries from across a wide spectrum of pre-analytical conditions specific to India would give greater clarity on control of procedural steps for a downstream application like NGS. Our findings provide preliminary insights into the mutational profile of key cancer-associated genes and form a foundation for the larger-scale analysis of Indian TNBCs.


The authors would like to thank Tata Trusts (Mumbai, India) for generous support for conducting this research study. Research activities at Center for Translational Cancer Research (CTCR) are supported by Bajaj Auto Ltd. Recruitment of patients from Bangalore center was supported by a philanthropic grant from Nadathur Estates Pvt Ltd. Madhura Kulkarni is supported by Department of Biotechnology- Ramalingaswami “re-entry” fellowship awarded by DBT-India.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

 » References Top

Kulkarni A, Kelkar D, Parikh N, Shashidhara LS, Koppiker CB, Kulkarni M. Meta-analysis of prevalence of Triple Negative Breast Cancer and its clinical features at incidence in Indian Breast Cancer Patients. JCO Glob Oncol 2020;7:1052-60.  Back to cited text no. 1
Sandhu GS, Erqou S, Patterson H, Mathew A. Prevalence of triple-negative breast cancer in India: Systematic review and meta-analysis. J Glob Oncol 2016;2:412-21.  Back to cited text no. 2
Bianchini G, Balko JM, Mayer IA, Sanders ME, Gianni L. Triple-negative breast cancer: Challenges and opportunities of a heterogeneous disease. Nat Rev Clin Oncol 2016;13:674-90.  Back to cited text no. 3
Curtis C, Shah SP, Chin SF, Turashvili G, Rueda OM, Dunning MJ, et al. The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups. Nature 2012;486:346-52.  Back to cited text no. 4
Burstein MD, Tsimelzon A, Poage GM, Covington KR, Contreras A, Fuqua SAW, et al. Comprehensive genomic analysis identifies novel subtypes and targets of triple-negative breast cancer. Clin Cancer Res 2015;21:1688-98.  Back to cited text no. 5
Bailey MH, Tokheim C, Porta-Pardo E, Sengupta S, Bertrand D, Weerasinghe A, et al. Comprehensive characterization of cancer driver genes and mutations. Cell 2018;173:371-85.  Back to cited text no. 6
Jiang Y-Z, Ma D, Suo C, Shi J, Xue M, Hu X, et al. Genomic and transcriptomic landscape of triple-negative breast cancers: Subtypes and treatment strategies. Cancer Cell 2019;35:428-40.  Back to cited text no. 7
Koboldt DC, Fulton RS, McLellan MD, Schmidt H, Kalicki-Veizer J, McMichael JF, et al. Comprehensive molecular portraits of human breast tumours. Nature 2012;490:61-70.  Back to cited text no. 8
Uscanga-Perales GI, Santuario-Facio SK, Sanchez-Dominguez CN, Cardona-Huerta S, Muñoz-Maldonado GE, Ruiz-Flores P, et al. Genetic alterations of triple negative breast cancer (TNBC) in women from northeastern Mexico. Oncol Lett 2019;17:3581-8.  Back to cited text no. 9
Santarpia L, Qi Y, Stemke-Hale K, Wang B, Young EJ, Booser DJ, et al. Mutation profiling identifies numerous rare drug targets and distinct mutation patterns in different clinical subtypes of breast cancers. Breast Cancer Res Treat 2012;134:333-43.  Back to cited text no. 10
Yeh CH, Bellon M, Nicot C. FBXW7: A critical tumor suppressor of human cancers. Mol Cancer 2018;17:115.  Back to cited text no. 11
Zhang Q, Karnak D, Tan M, Lawrence TS, Morgan MA, Sun Y. FBXW7 facilitates nonhomologous end-joining via K63-linked polyubiquitylation of XRCC4. Mol Cell 2016;61:419-33.  Back to cited text no. 12
Niihori T, Aoki Y, Ohashi H, Kurosawa K, Kondoh T, Ishikiriyama S, et al. Functional analysis of PTPN11/SHP-2 mutants identified in Noonan syndrome and childhood leukemia. J Hum Genet 2005;50:192-202.  Back to cited text no. 13
Aceto N, Sausgruber N, Brinkhaus H, Gaidatzis D, Martiny-Baron G, Mazzarol G, et al. Tyrosine phosphatase SHP2 promotes breast cancer progression and maintains tumor-initiating cells via activation of key transcription factors and a positive feedback signaling loop. Nat Med 2012;18:529-37.  Back to cited text no. 14
Sausgruber N, Coissieux MM, Britschgi A, Wyckoff J, Aceto N, Leroy C, et al. Tyrosine phosphatase SHP2 increases cell motility in triple-negative breast cancer through the activation of SRC-family kinases. Oncogene 2015;34:2272-8.  Back to cited text no. 15
Malinge S, Ragu C, Della-Valle V, Pisani D, Constantinescu SN, Perez C, et al. Activating mutations in human acute megakaryoblastic leukemia. Blood 2008;112:4220-6.  Back to cited text no. 16
Walters DK, Mercher T, Gu TL, O'Hare T, Tyner JW, Loriaux M, et al. Activating alleles of JAK3 in acute megakaryoblastic leukemia. Cancer Cell 2006;10:65-75.  Back to cited text no. 17
U MC, Talevich E, Katiyar S, Rasheed K, Kannan N. Prediction and prioritization of rare oncogenic mutations in the cancer kinome using novel features and multiple classifiers. PLoS Comput Biol 2014;10:e1003545.  Back to cited text no. 18
Cossu-Rocca P, Orrù S, Muroni MR, Sanges F, Sotgiu G, Ena S, et al. Analysis of PIK3CA mutations and activation pathways in triple negative breast cancer. PLoS One 2015;10:e0141763.  Back to cited text no. 19
Ding L, Bailey MH, Porta-Pardo E, Thorsson V, Colaprico A, Bertrand D, et al. Perspective on oncogenic processes at the end of the beginning of cancer genomics. Cell 2018;173:305-20.  Back to cited text no. 20


  [Figure 1], [Figure 2], [Figure 3]

  [Table 1]


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