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Abstract P3-08-07: Comparison of the genomic alterations in metastatic inflammatory and non-inflammatory breast cancer
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Abstract
Background:. Inflammatory breast cancer (IBC) represents a rare (~1-5% of all breast cancers, BC) and particularly aggressive type of BC, accounting for roughly 10% of BC-related mortality annually. So far IBC has been mainly characterized at the genomic level using samples from the primary tumor. Here, using publicly available data from two large cohorts, we compared the genomic alterations in primary and metastatic samples from patients with metastatic IBC to alterations in samples of patients with metastatic non-IBC. Patients and methods:. We retrieved publicly available clinical and genomic data from primary (P) and metastatic (M) samples from MSK-IMPACT (MSK) and the Metastatic Breast Cancer project (MBC) from cbioportal. IBC was defined as cT4d. We considered female metastatic patients with invasive BC of no special type (commonly referred to as invasive ductal BC): 34 patients with IBC and 602 with non-IBC. To focus on alterations with potential clinical relevance, we only retained the genomic alterations annotated as oncogenic by OncoKB. We applied Firth logistic regression adjusted for hormonal receptor status (positive vs negative), HER2 status (positive vs negative) stage (II vs I, III vs I, IV vs I) and cohort (MSK vs MBC) with genomic alterations or metastatic sites as outcome variables and IBC status as independent variable (yes vs no). A minimum of 5 patients harboring the alterations were required to perform the analysis. Chromosomal instability (CIN) score and Tumor Mutational Burden (TMB) were investigated by linear regression and quantile regression respectively, adjusted as described above and considering the median for the latest. P and M samples were analyzed separately, a patient was considered as ‘having’ the alteration if at least one of her samples was altered. All analyses were performed in R 4.0.2. Results:. Metastatic samples from chest wall and skin metastases were significantly more represented in patients with IBC as compared to patients with non-IBC (Adjusted Odds Ratio (ORadj): 6.16, 95% confidence interval (95CI): [1.94-18.38], p-value: .003 and ORadj: 7.60, 95CI: [1.66-30.05], p-value: .012 respectively), which is in line with the course of the IBC disease. Several studies have suggested IBC to have a higher TMB than non-IBC. Here we confirmed an increase in TMB in P and M IBC (Adjusted coefficient (coefadj): 3.00, 95CI: [1.60-4.20], p-value: .003 and coefadj: 4.00, 95CI: [0.85-4.15], p-value<.001). On the contrary, we did not observe an increase in CIN score in patient with IBC as compared to patient with non-IBC, both when considering P and M samples (coefadj: -.001, 95CI: [-0.10;0.09], p-value: .877 and coefadj: -.05, 95CI: [-0.16;0.05], p-value: .330 respectively). With regard to the genomic alterations, we observed an increased frequency of TP53 mutations as well as amplifications of AURKA and FGFR1 in patients with IBC versus patient with non-IBC both considering P and M samples (Table 1). We also observed an increased prevalence of PIK3CA and GATA3 mutations in patients with IBC versus non-IBC in the M samples only. Conclusion:. While the results need to be validated in additional patient series, these could be of potential clinical relevance given the higher incidence of treatment targets (AURKA amplifications, PIK3CA mutations) and markers of treatment resistance (FGFR1 amplifications) present in IBC versus non-IBC in patients with metastatic disease.
Table 1.Patients with primary samples. (279 patients with clinical information available - 279 samples)Patients with metastatic samples. (311 patients with clinical information available - 339 samples)AlterationAlteration countOR [95CI]p-valueAlteration countOR [95CI]p-valueTP53 mutation4120.18 [4.95-96.38]<.0013511.30 [3.68 - 37.05]<.001PIK3CA mutation106.00 [0.76-40.27].085156.35 [1.58-22.61].011GATA3 mutation85.10 [0.49-30.63].147610.95 [1.59 - 62.80].018AURKA amplification539.33 [5.26-490.37]<.001517.28 [2.76-119.06]<.001FGFR1 amplification98.99 [1.81-40.52].009714.08 [2.63-71.46]<.001
Citation Format: François Richard, Maxim De Schepper, Marion Maetens, Sophia Leduc, Edoardo Isnaldi, Tatjana Geukens, Karen Van Baelen, Ha-Linh Nguyen, Peter Vermeulen, Steven Van Laere, Luc Dirix, Giuseppe Floris, Elia Biganzoli, Christine Desmedt. Comparison of the genomic alterations in metastatic inflammatory and non-inflammatory breast cancer [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P3-08-07.
American Association for Cancer Research (AACR)
Title: Abstract P3-08-07: Comparison of the genomic alterations in metastatic inflammatory and non-inflammatory breast cancer
Description:
Abstract
Background:.
Inflammatory breast cancer (IBC) represents a rare (~1-5% of all breast cancers, BC) and particularly aggressive type of BC, accounting for roughly 10% of BC-related mortality annually.
So far IBC has been mainly characterized at the genomic level using samples from the primary tumor.
Here, using publicly available data from two large cohorts, we compared the genomic alterations in primary and metastatic samples from patients with metastatic IBC to alterations in samples of patients with metastatic non-IBC.
Patients and methods:.
We retrieved publicly available clinical and genomic data from primary (P) and metastatic (M) samples from MSK-IMPACT (MSK) and the Metastatic Breast Cancer project (MBC) from cbioportal.
IBC was defined as cT4d.
We considered female metastatic patients with invasive BC of no special type (commonly referred to as invasive ductal BC): 34 patients with IBC and 602 with non-IBC.
To focus on alterations with potential clinical relevance, we only retained the genomic alterations annotated as oncogenic by OncoKB.
We applied Firth logistic regression adjusted for hormonal receptor status (positive vs negative), HER2 status (positive vs negative) stage (II vs I, III vs I, IV vs I) and cohort (MSK vs MBC) with genomic alterations or metastatic sites as outcome variables and IBC status as independent variable (yes vs no).
A minimum of 5 patients harboring the alterations were required to perform the analysis.
Chromosomal instability (CIN) score and Tumor Mutational Burden (TMB) were investigated by linear regression and quantile regression respectively, adjusted as described above and considering the median for the latest.
P and M samples were analyzed separately, a patient was considered as ‘having’ the alteration if at least one of her samples was altered.
All analyses were performed in R 4.
2.
Results:.
Metastatic samples from chest wall and skin metastases were significantly more represented in patients with IBC as compared to patients with non-IBC (Adjusted Odds Ratio (ORadj): 6.
16, 95% confidence interval (95CI): [1.
94-18.
38], p-value: .
003 and ORadj: 7.
60, 95CI: [1.
66-30.
05], p-value: .
012 respectively), which is in line with the course of the IBC disease.
Several studies have suggested IBC to have a higher TMB than non-IBC.
Here we confirmed an increase in TMB in P and M IBC (Adjusted coefficient (coefadj): 3.
00, 95CI: [1.
60-4.
20], p-value: .
003 and coefadj: 4.
00, 95CI: [0.
85-4.
15], p-value<.
001).
On the contrary, we did not observe an increase in CIN score in patient with IBC as compared to patient with non-IBC, both when considering P and M samples (coefadj: -.
001, 95CI: [-0.
10;0.
09], p-value: .
877 and coefadj: -.
05, 95CI: [-0.
16;0.
05], p-value: .
330 respectively).
With regard to the genomic alterations, we observed an increased frequency of TP53 mutations as well as amplifications of AURKA and FGFR1 in patients with IBC versus patient with non-IBC both considering P and M samples (Table 1).
We also observed an increased prevalence of PIK3CA and GATA3 mutations in patients with IBC versus non-IBC in the M samples only.
Conclusion:.
While the results need to be validated in additional patient series, these could be of potential clinical relevance given the higher incidence of treatment targets (AURKA amplifications, PIK3CA mutations) and markers of treatment resistance (FGFR1 amplifications) present in IBC versus non-IBC in patients with metastatic disease.
Table 1.
Patients with primary samples.
(279 patients with clinical information available - 279 samples)Patients with metastatic samples.
(311 patients with clinical information available - 339 samples)AlterationAlteration countOR [95CI]p-valueAlteration countOR [95CI]p-valueTP53 mutation4120.
18 [4.
95-96.
38]<.
0013511.
30 [3.
68 - 37.
05]<.
001PIK3CA mutation106.
00 [0.
76-40.
27].
085156.
35 [1.
58-22.
61].
011GATA3 mutation85.
10 [0.
49-30.
63].
147610.
95 [1.
59 - 62.
80].
018AURKA amplification539.
33 [5.
26-490.
37]<.
001517.
28 [2.
76-119.
06]<.
001FGFR1 amplification98.
99 [1.
81-40.
52].
009714.
08 [2.
63-71.
46]<.
001
Citation Format: François Richard, Maxim De Schepper, Marion Maetens, Sophia Leduc, Edoardo Isnaldi, Tatjana Geukens, Karen Van Baelen, Ha-Linh Nguyen, Peter Vermeulen, Steven Van Laere, Luc Dirix, Giuseppe Floris, Elia Biganzoli, Christine Desmedt.
Comparison of the genomic alterations in metastatic inflammatory and non-inflammatory breast cancer [abstract].
In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX.
Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P3-08-07.
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