Background

The Triple-Negative Breast Cancer (TNBC) molecular subtyping and target identification based on Immunohistochemistry (IHC) is of considerable worth for routine use. Yet, literature on this topic is limited worldwide and needs to be enriched with data from different populations.

Methods

We assessed the IHC expression of subtyping biomarkers (Cytokeratins 5, 14 and 17, Epidermal Growth Factor Receptor, Claudins 3 and 7, E-cadherin, Vimentin and Androgen receptor) and predictive biomarkers (Tumor-infiltrating lymphocytes (TILs) density, Breast Cancer Antigen 1 (BRCA1) and P53) in a cohort of TNBC patients. Clinicopathologic parameters and overall survival (OS) were investigated as well.

Results

The patients were aged 50.11 ± 12.13y (more than 40y in 76.56% of patients), and 23.44% had a BC family history. They were in a non-advanced stage: 51.6% T2 stage, 56.2% negative lymph node involvement, 76.6% without metastasis and 64.1% grade II Scarff-Bloom-Richardson classification (SBR).

The IHC subtypes were: 53.1% Basal-like1 (BL1), 6.3% Basal-like2 (BL2), 17.2% Mesenchymal (MES), 9.4% Luminal Androgen Receptor (LAR), 4.7% Mixed subtype and 9.4% “Unclassified” type. The LAR subtype involved the youngest patients (40.17 ± 8.68y, p = 0.02). The “Unclassified” subtype expressed the p53 mutated-type pattern more frequently (100%, p = 0.07). The BRCA1 mutated pattern and TILs infiltration were present in (23.44% and 37.5% of patients, respectively).

The OS of the subtypes differed significantly (p = 0.007, log-rank test). The subtypes median OS were, respectively, 15.47 mo. (Unclassified), 18.94 mo. (BL2), 27.23 mo. (MES), 27.28 mo. (Mixed), 30.88 mo. (BL1), and 45.07 mo. (LAR). There was no difference in the OS following age, BRCA1 expression, p53 pattern and TILs density. Though, the OS following the TNM stage was different (p = 0.001). A multivariable Cox proportional hazards regression analysis showed that TNM staging and TNBC subtypes, independently influence the OS (p < 0.001 and p = 0.017, respectively).

Hence, IHC is useful in TNBC subtyping for prognostic purposes and in the identification of therapeutic biomarkers. Further investigation is required to confirm our results and to implement IHC as a routine tool to improve patient’s care.

Background

The Triple-Negative Breast Cancer (TNBC) molecular subtyping and target identification based on Immunohistochemistry (IHC) is of considerable worth for routine use. Yet, literature on this topic is limited worldwide and needs to be enriched with data from different populations.

Methods

We assessed the IHC expression of subtyping biomarkers (Cytokeratins 5, 14 and 17, Epidermal Growth Factor Receptor, Claudins 3 and 7, E-cadherin, Vimentin and Androgen receptor) and predictive biomarkers (Tumor-infiltrating lymphocytes (TILs) density, Breast Cancer Antigen 1 (BRCA1) and P53) in a cohort of TNBC patients. Clinicopathologic parameters and overall survival (OS) were investigated as well.

Results

The patients were aged 50.11 ± 12.13y (more than 40y in 76.56% of patients), and 23.44% had a BC family history. They were in a non-advanced stage: 51.6% T2 stage, 56.2% negative lymph node involvement, 76.6% without metastasis and 64.1% grade II Scarff-Bloom-Richardson classification (SBR).

The IHC subtypes were: 53.1% Basal-like1 (BL1), 6.3% Basal-like2 (BL2), 17.2% Mesenchymal (MES), 9.4% Luminal Androgen Receptor (LAR), 4.7% Mixed subtype and 9.4% “Unclassified” type. The LAR subtype involved the youngest patients (40.17 ± 8.68y, p = 0.02). The “Unclassified” subtype expressed the p53 mutated-type pattern more frequently (100%, p = 0.07). The BRCA1 mutated pattern and TILs infiltration were present in (23.44% and 37.5% of patients, respectively).

The OS of the subtypes differed significantly (p = 0.007, log-rank test). The subtypes median OS were, respectively, 15.47 mo. (Unclassified), 18.94 mo. (BL2), 27.23 mo. (MES), 27.28 mo. (Mixed), 30.88 mo. (BL1), and 45.07 mo. (LAR). There was no difference in the OS following age, BRCA1 expression, p53 pattern and TILs density. Though, the OS following the TNM stage was different (p = 0.001). A multivariable Cox proportional hazards regression analysis showed that TNM staging and TNBC subtypes, independently influence the OS (p < 0.001 and p = 0.017, respectively).

Hence, IHC is useful in TNBC subtyping for prognostic purposes and in the identification of therapeutic biomarkers. Further investigation is required to confirm our results and to implement IHC as a routine tool to improve patient’s care.

Background

The Triple-Negative Breast Cancer (TNBC) molecular subtyping and target identification based on Immunohistochemistry (IHC) is of considerable worth for routine use. Yet, literature on this topic is limited worldwide and needs to be enriched with data from different populations.

Methods

We assessed the IHC expression of subtyping biomarkers (Cytokeratins 5, 14 and 17, Epidermal Growth Factor Receptor, Claudins 3 and 7, E-cadherin, Vimentin and Androgen receptor) and predictive biomarkers (Tumor-infiltrating lymphocytes (TILs) density, Breast Cancer Antigen 1 (BRCA1) and P53) in a cohort of TNBC patients. Clinicopathologic parameters and overall survival (OS) were investigated as well.

Results

The patients were aged 50.11 ± 12.13y (more than 40y in 76.56% of patients), and 23.44% had a BC family history. They were in a non-advanced stage: 51.6% T2 stage, 56.2% negative lymph node involvement, 76.6% without metastasis and 64.1% grade II Scarff-Bloom-Richardson classification (SBR).

The IHC subtypes were: 53.1% Basal-like1 (BL1), 6.3% Basal-like2 (BL2), 17.2% Mesenchymal (MES), 9.4% Luminal Androgen Receptor (LAR), 4.7% Mixed subtype and 9.4% “Unclassified” type. The LAR subtype involved the youngest patients (40.17 ± 8.68y, p = 0.02). The “Unclassified” subtype expressed the p53 mutated-type pattern more frequently (100%, p = 0.07). The BRCA1 mutated pattern and TILs infiltration were present in (23.44% and 37.5% of patients, respectively).

The OS of the subtypes differed significantly (p = 0.007, log-rank test). The subtypes median OS were, respectively, 15.47 mo. (Unclassified), 18.94 mo. (BL2), 27.23 mo. (MES), 27.28 mo. (Mixed), 30.88 mo. (BL1), and 45.07 mo. (LAR). There was no difference in the OS following age, BRCA1 expression, p53 pattern and TILs density. Though, the OS following the TNM stage was different (p = 0.001). A multivariable Cox proportional hazards regression analysis showed that TNM staging and TNBC subtypes, independently influence the OS (p < 0.001 and p = 0.017, respectively).

Hence, IHC is useful in TNBC subtyping for prognostic purposes and in the identification of therapeutic biomarkers. Further investigation is required to confirm our results and to implement IHC as a routine tool to improve patient’s care.

Background

The Triple-Negative Breast Cancer (TNBC) molecular subtyping and target identification based on Immunohistochemistry (IHC) is of considerable worth for routine use. Yet, literature on this topic is limited worldwide and needs to be enriched with data from different populations.

Methods

We assessed the IHC expression of subtyping biomarkers (Cytokeratins 5, 14 and 17, Epidermal Growth Factor Receptor, Claudins 3 and 7, E-cadherin, Vimentin and Androgen receptor) and predictive biomarkers (Tumor-infiltrating lymphocytes (TILs) density, Breast Cancer Antigen 1 (BRCA1) and P53) in a cohort of TNBC patients. Clinicopathologic parameters and overall survival (OS) were investigated as well.

Results

The patients were aged 50.11 ± 12.13y (more than 40y in 76.56% of patients), and 23.44% had a BC family history. They were in a non-advanced stage: 51.6% T2 stage, 56.2% negative lymph node involvement, 76.6% without metastasis and 64.1% grade II Scarff-Bloom-Richardson classification (SBR).

The IHC subtypes were: 53.1% Basal-like1 (BL1), 6.3% Basal-like2 (BL2), 17.2% Mesenchymal (MES), 9.4% Luminal Androgen Receptor (LAR), 4.7% Mixed subtype and 9.4% “Unclassified” type. The LAR subtype involved the youngest patients (40.17 ± 8.68y, p = 0.02). The “Unclassified” subtype expressed the p53 mutated-type pattern more frequently (100%, p = 0.07). The BRCA1 mutated pattern and TILs infiltration were present in (23.44% and 37.5% of patients, respectively).

The OS of the subtypes differed significantly (p = 0.007, log-rank test). The subtypes median OS were, respectively, 15.47 mo. (Unclassified), 18.94 mo. (BL2), 27.23 mo. (MES), 27.28 mo. (Mixed), 30.88 mo. (BL1), and 45.07 mo. (LAR). There was no difference in the OS following age, BRCA1 expression, p53 pattern and TILs density. Though, the OS following the TNM stage was different (p = 0.001). A multivariable Cox proportional hazards regression analysis showed that TNM staging and TNBC subtypes, independently influence the OS (p < 0.001 and p = 0.017, respectively).

Hence, IHC is useful in TNBC subtyping for prognostic purposes and in the identification of therapeutic biomarkers. Further investigation is required to confirm our results and to implement IHC as a routine tool to improve patient’s care.

Background

The Triple-Negative Breast Cancer (TNBC) molecular subtyping and target identification based on Immunohistochemistry (IHC) is of considerable worth for routine use. Yet, literature on this topic is limited worldwide and needs to be enriched with data from different populations.

Methods

We assessed the IHC expression of subtyping biomarkers (Cytokeratins 5, 14 and 17, Epidermal Growth Factor Receptor, Claudins 3 and 7, E-cadherin, Vimentin and Androgen receptor) and predictive biomarkers (Tumor-infiltrating lymphocytes (TILs) density, Breast Cancer Antigen 1 (BRCA1) and P53) in a cohort of TNBC patients. Clinicopathologic parameters and overall survival (OS) were investigated as well.

Results

The patients were aged 50.11 ± 12.13y (more than 40y in 76.56% of patients), and 23.44% had a BC family history. They were in a non-advanced stage: 51.6% T2 stage, 56.2% negative lymph node involvement, 76.6% without metastasis and 64.1% grade II Scarff-Bloom-Richardson classification (SBR).

The IHC subtypes were: 53.1% Basal-like1 (BL1), 6.3% Basal-like2 (BL2), 17.2% Mesenchymal (MES), 9.4% Luminal Androgen Receptor (LAR), 4.7% Mixed subtype and 9.4% “Unclassified” type. The LAR subtype involved the youngest patients (40.17 ± 8.68y, p = 0.02). The “Unclassified” subtype expressed the p53 mutated-type pattern more frequently (100%, p = 0.07). The BRCA1 mutated pattern and TILs infiltration were present in (23.44% and 37.5% of patients, respectively).

The OS of the subtypes differed significantly (p = 0.007, log-rank test). The subtypes median OS were, respectively, 15.47 mo. (Unclassified), 18.94 mo. (BL2), 27.23 mo. (MES), 27.28 mo. (Mixed), 30.88 mo. (BL1), and 45.07 mo. (LAR). There was no difference in the OS following age, BRCA1 expression, p53 pattern and TILs density. Though, the OS following the TNM stage was different (p = 0.001). A multivariable Cox proportional hazards regression analysis showed that TNM staging and TNBC subtypes, independently influence the OS (p < 0.001 and p = 0.017, respectively).

Hence, IHC is useful in TNBC subtyping for prognostic purposes and in the identification of therapeutic biomarkers. Further investigation is required to confirm our results and to implement IHC as a routine tool to improve patient’s care.

Background

The Triple-Negative Breast Cancer (TNBC) molecular subtyping and target identification based on Immunohistochemistry (IHC) is of considerable worth for routine use. Yet, literature on this topic is limited worldwide and needs to be enriched with data from different populations.

Methods

We assessed the IHC expression of subtyping biomarkers (Cytokeratins 5, 14 and 17, Epidermal Growth Factor Receptor, Claudins 3 and 7, E-cadherin, Vimentin and Androgen receptor) and predictive biomarkers (Tumor-infiltrating lymphocytes (TILs) density, Breast Cancer Antigen 1 (BRCA1) and P53) in a cohort of TNBC patients. Clinicopathologic parameters and overall survival (OS) were investigated as well.

Results

The patients were aged 50.11 ± 12.13y (more than 40y in 76.56% of patients), and 23.44% had a BC family history. They were in a non-advanced stage: 51.6% T2 stage, 56.2% negative lymph node involvement, 76.6% without metastasis and 64.1% grade II Scarff-Bloom-Richardson classification (SBR).

The IHC subtypes were: 53.1% Basal-like1 (BL1), 6.3% Basal-like2 (BL2), 17.2% Mesenchymal (MES), 9.4% Luminal Androgen Receptor (LAR), 4.7% Mixed subtype and 9.4% “Unclassified” type. The LAR subtype involved the youngest patients (40.17 ± 8.68y, p = 0.02). The “Unclassified” subtype expressed the p53 mutated-type pattern more frequently (100%, p = 0.07). The BRCA1 mutated pattern and TILs infiltration were present in (23.44% and 37.5% of patients, respectively).

The OS of the subtypes differed significantly (p = 0.007, log-rank test). The subtypes median OS were, respectively, 15.47 mo. (Unclassified), 18.94 mo. (BL2), 27.23 mo. (MES), 27.28 mo. (Mixed), 30.88 mo. (BL1), and 45.07 mo. (LAR). There was no difference in the OS following age, BRCA1 expression, p53 pattern and TILs density. Though, the OS following the TNM stage was different (p = 0.001). A multivariable Cox proportional hazards regression analysis showed that TNM staging and TNBC subtypes, independently influence the OS (p < 0.001 and p = 0.017, respectively).

Hence, IHC is useful in TNBC subtyping for prognostic purposes and in the identification of therapeutic biomarkers. Further investigation is required to confirm our results and to implement IHC as a routine tool to improve patient’s care.

Background

The Triple-Negative Breast Cancer (TNBC) molecular subtyping and target identification based on Immunohistochemistry (IHC) is of considerable worth for routine use. Yet, literature on this topic is limited worldwide and needs to be enriched with data from different populations.

Methods

We assessed the IHC expression of subtyping biomarkers (Cytokeratins 5, 14 and 17, Epidermal Growth Factor Receptor, Claudins 3 and 7, E-cadherin, Vimentin and Androgen receptor) and predictive biomarkers (Tumor-infiltrating lymphocytes (TILs) density, Breast Cancer Antigen 1 (BRCA1) and P53) in a cohort of TNBC patients. Clinicopathologic parameters and overall survival (OS) were investigated as well.

Results

The patients were aged 50.11 ± 12.13y (more than 40y in 76.56% of patients), and 23.44% had a BC family history. They were in a non-advanced stage: 51.6% T2 stage, 56.2% negative lymph node involvement, 76.6% without metastasis and 64.1% grade II Scarff-Bloom-Richardson classification (SBR).

The IHC subtypes were: 53.1% Basal-like1 (BL1), 6.3% Basal-like2 (BL2), 17.2% Mesenchymal (MES), 9.4% Luminal Androgen Receptor (LAR), 4.7% Mixed subtype and 9.4% “Unclassified” type. The LAR subtype involved the youngest patients (40.17 ± 8.68y, p = 0.02). The “Unclassified” subtype expressed the p53 mutated-type pattern more frequently (100%, p = 0.07). The BRCA1 mutated pattern and TILs infiltration were present in (23.44% and 37.5% of patients, respectively).

The OS of the subtypes differed significantly (p = 0.007, log-rank test). The subtypes median OS were, respectively, 15.47 mo. (Unclassified), 18.94 mo. (BL2), 27.23 mo. (MES), 27.28 mo. (Mixed), 30.88 mo. (BL1), and 45.07 mo. (LAR). There was no difference in the OS following age, BRCA1 expression, p53 pattern and TILs density. Though, the OS following the TNM stage was different (p = 0.001). A multivariable Cox proportional hazards regression analysis showed that TNM staging and TNBC subtypes, independently influence the OS (p < 0.001 and p = 0.017, respectively).

Hence, IHC is useful in TNBC subtyping for prognostic purposes and in the identification of therapeutic biomarkers. Further investigation is required to confirm our results and to implement IHC as a routine tool to improve patient’s care.

Background

The Triple-Negative Breast Cancer (TNBC) molecular subtyping and target identification based on Immunohistochemistry (IHC) is of considerable worth for routine use. Yet, literature on this topic is limited worldwide and needs to be enriched with data from different populations.

Methods

We assessed the IHC expression of subtyping biomarkers (Cytokeratins 5, 14 and 17, Epidermal Growth Factor Receptor, Claudins 3 and 7, E-cadherin, Vimentin and Androgen receptor) and predictive biomarkers (Tumor-infiltrating lymphocytes (TILs) density, Breast Cancer Antigen 1 (BRCA1) and P53) in a cohort of TNBC patients. Clinicopathologic parameters and overall survival (OS) were investigated as well.

Results

The patients were aged 50.11 ± 12.13y (more than 40y in 76.56% of patients), and 23.44% had a BC family history. They were in a non-advanced stage: 51.6% T2 stage, 56.2% negative lymph node involvement, 76.6% without metastasis and 64.1% grade II Scarff-Bloom-Richardson classification (SBR).

The IHC subtypes were: 53.1% Basal-like1 (BL1), 6.3% Basal-like2 (BL2), 17.2% Mesenchymal (MES), 9.4% Luminal Androgen Receptor (LAR), 4.7% Mixed subtype and 9.4% “Unclassified” type. The LAR subtype involved the youngest patients (40.17 ± 8.68y, p = 0.02). The “Unclassified” subtype expressed the p53 mutated-type pattern more frequently (100%, p = 0.07). The BRCA1 mutated pattern and TILs infiltration were present in (23.44% and 37.5% of patients, respectively).

The OS of the subtypes differed significantly (p = 0.007, log-rank test). The subtypes median OS were, respectively, 15.47 mo. (Unclassified), 18.94 mo. (BL2), 27.23 mo. (MES), 27.28 mo. (Mixed), 30.88 mo. (BL1), and 45.07 mo. (LAR). There was no difference in the OS following age, BRCA1 expression, p53 pattern and TILs density. Though, the OS following the TNM stage was different (p = 0.001). A multivariable Cox proportional hazards regression analysis showed that TNM staging and TNBC subtypes, independently influence the OS (p < 0.001 and p = 0.017, respectively).

Hence, IHC is useful in TNBC subtyping for prognostic purposes and in the identification of therapeutic biomarkers. Further investigation is required to confirm our results and to implement IHC as a routine tool to improve patient’s care.

Background

The Triple-Negative Breast Cancer (TNBC) molecular subtyping and target identification based on Immunohistochemistry (IHC) is of considerable worth for routine use. Yet, literature on this topic is limited worldwide and needs to be enriched with data from different populations.

Methods

We assessed the IHC expression of subtyping biomarkers (Cytokeratins 5, 14 and 17, Epidermal Growth Factor Receptor, Claudins 3 and 7, E-cadherin, Vimentin and Androgen receptor) and predictive biomarkers (Tumor-infiltrating lymphocytes (TILs) density, Breast Cancer Antigen 1 (BRCA1) and P53) in a cohort of TNBC patients. Clinicopathologic parameters and overall survival (OS) were investigated as well.

Results

The patients were aged 50.11 ± 12.13y (more than 40y in 76.56% of patients), and 23.44% had a BC family history. They were in a non-advanced stage: 51.6% T2 stage, 56.2% negative lymph node involvement, 76.6% without metastasis and 64.1% grade II Scarff-Bloom-Richardson classification (SBR).

The IHC subtypes were: 53.1% Basal-like1 (BL1), 6.3% Basal-like2 (BL2), 17.2% Mesenchymal (MES), 9.4% Luminal Androgen Receptor (LAR), 4.7% Mixed subtype and 9.4% “Unclassified” type. The LAR subtype involved the youngest patients (40.17 ± 8.68y, p = 0.02). The “Unclassified” subtype expressed the p53 mutated-type pattern more frequently (100%, p = 0.07). The BRCA1 mutated pattern and TILs infiltration were present in (23.44% and 37.5% of patients, respectively).

The OS of the subtypes differed significantly (p = 0.007, log-rank test). The subtypes median OS were, respectively, 15.47 mo. (Unclassified), 18.94 mo. (BL2), 27.23 mo. (MES), 27.28 mo. (Mixed), 30.88 mo. (BL1), and 45.07 mo. (LAR). There was no difference in the OS following age, BRCA1 expression, p53 pattern and TILs density. Though, the OS following the TNM stage was different (p = 0.001). A multivariable Cox proportional hazards regression analysis showed that TNM staging and TNBC subtypes, independently influence the OS (p < 0.001 and p = 0.017, respectively).

Hence, IHC is useful in TNBC subtyping for prognostic purposes and in the identification of therapeutic biomarkers. Further investigation is required to confirm our results and to implement IHC as a routine tool to improve patient’s care.

Background

The Triple-Negative Breast Cancer (TNBC) molecular subtyping and target identification based on Immunohistochemistry (IHC) is of considerable worth for routine use. Yet, literature on this topic is limited worldwide and needs to be enriched with data from different populations.

Methods

We assessed the IHC expression of subtyping biomarkers (Cytokeratins 5, 14 and 17, Epidermal Growth Factor Receptor, Claudins 3 and 7, E-cadherin, Vimentin and Androgen receptor) and predictive biomarkers (Tumor-infiltrating lymphocytes (TILs) density, Breast Cancer Antigen 1 (BRCA1) and P53) in a cohort of TNBC patients. Clinicopathologic parameters and overall survival (OS) were investigated as well.

Results

The patients were aged 50.11 ± 12.13y (more than 40y in 76.56% of patients), and 23.44% had a BC family history. They were in a non-advanced stage: 51.6% T2 stage, 56.2% negative lymph node involvement, 76.6% without metastasis and 64.1% grade II Scarff-Bloom-Richardson classification (SBR).

The IHC subtypes were: 53.1% Basal-like1 (BL1), 6.3% Basal-like2 (BL2), 17.2% Mesenchymal (MES), 9.4% Luminal Androgen Receptor (LAR), 4.7% Mixed subtype and 9.4% “Unclassified” type. The LAR subtype involved the youngest patients (40.17 ± 8.68y, p = 0.02). The “Unclassified” subtype expressed the p53 mutated-type pattern more frequently (100%, p = 0.07). The BRCA1 mutated pattern and TILs infiltration were present in (23.44% and 37.5% of patients, respectively).

The OS of the subtypes differed significantly (p = 0.007, log-rank test). The subtypes median OS were, respectively, 15.47 mo. (Unclassified), 18.94 mo. (BL2), 27.23 mo. (MES), 27.28 mo. (Mixed), 30.88 mo. (BL1), and 45.07 mo. (LAR). There was no difference in the OS following age, BRCA1 expression, p53 pattern and TILs density. Though, the OS following the TNM stage was different (p = 0.001). A multivariable Cox proportional hazards regression analysis showed that TNM staging and TNBC subtypes, independently influence the OS (p < 0.001 and p = 0.017, respectively).

Hence, IHC is useful in TNBC subtyping for prognostic purposes and in the identification of therapeutic biomarkers. Further investigation is required to confirm our results and to implement IHC as a routine tool to improve patient’s care.

This study set out to examine the thermo-mechanical behavior of gypsum-protected steel columns (GPSC) exposed to fire, including the cooling phase, through numerical analyses with the aim of better understanding the effect of protection materials and identifying the possibility of delayed failure of GPSC during this critical period. A parametric study has been performed with the SAFIR program using a sequentially decoupled thermal structural analysis. The examined factors are the shape of the columns, the fire intensity, and the thickness of the protection. Gypsum serves as insulation, providing passive protection to prevent the degradation of steel mechanical properties and to mitigate and delay the collapse of steel columns during fire exposure. Different thicknesses of gypsum were considered (1 mm, 3 mm, and 5 mm) in order to analyze the effect of the rate of heat storage on the delayed collapse during and after fire exposure. The simulations were performed considering ISO fire and parametric temperature–time curves, which include a cooling regime that is linear. The findings show that the failure of the GPSC over the period of cooling is a possible event where the protection acts as a cooling retarder, which leads to a delayed collapse. Columns with massive sections and thick layers of protection are the most susceptible to delayed failure. Overall, this paper provides a real assessment of the load capacity in a natural fire situation, and the results highlight the possibility of delayed collapse of GPSC.