Triple Negative Breast Cancer Data Analysis PDF

*Bioscience* **Triple Negative Breast Cancer Data Analysis** **Roxana Olteanu, ** 1. Research Methods and Applications BIOL 3009, TU751/3 2. Dr Sean Kennedy and Dr Kathleen Brosnan 3. Technological University Dublin, Grangegorman, Co. Dublin, Ireland **Abstract** *Genetic mutations occur i...

*Bioscience* **Triple Negative Breast Cancer Data Analysis** **Roxana Olteanu, ** 1. Research Methods and Applications BIOL 3009, TU751/3 2. Dr Sean Kennedy and Dr Kathleen Brosnan 3. Technological University Dublin, Grangegorman, Co. Dublin, Ireland **Abstract** *Genetic mutations occur in the human body daily, however; some of these genetic mutations can have detrimental effects, such as tumour formations. Triple Negative Breast Cancer (TNBC) is an aggressive form of Breast Cancer (BC), which is lacking the expression of three receptors; Estrogen Receptor (ER), Progesterone Receptor (PR) and Human Epidermal Growth Factor 2 (HER2). As a result of TNBC lacking in these specific receptor expressions, other biomarkers have to be investigated in order to aid medical professionals in faster and more accurate detection of TNBC.* *This paper studies the data analysis, which is obtained from 30 patients with TNBC, who have mutations in BRCA1 and BRCA2 genes, with h focus on exploring potential biomarkers. A short examination also observes hot-spot mutations in; AKT- serine/threonine kinase 1 (AKT1), Ataxia-telangiectasia mutation (ATM), kinase insert domain receptor (KDR), receptor tyrosine kinase (KIT), phosphatidylinositol-4,5-bisphosthate 3-kinase catalytic subunit alpha (human) (PIK3CA), and tumour protein 53 (TP53), as per the statistical data provided by Technological University Dublin (TUD). This paper is a data investigation which aims to research the correlation between the different gene mutations, tumour progression, hot-spot mutations, and survival rate for patients with tumour metastasis (Mets).* 1. ***Introduction*** *It is a well-known fact that cancer in general, is specific to the patient due to the endless possibilities of mutations that occur in the body; which is why finding a blanket-like "cure for cancer" has been an ongoing issue. However, specific biomarkers have helped medical professionals with aiming for specific targets, finding common ground with similar cancer types, and hence, encouraging treatments. Due to the nature of TNBC, chemotherapy and other highly specific therapeutic agents are the foremost forms of treatment, where tumours have had a positive response to treatment. (Vagia et al., 2020).* *In accordance with recent studies, the consensus states that TNBC makes up an average of 10 - 20% of invasive BC, and a deeper investigation suggests that 15 -- 25% of TNBC patients carry a mutation in the BRCA1 and BRCA2 genes (Pareja et al., 2016)(Pavese et al., 2022). These statements are analysed with respect to the data provided by TUD in this paper.* *In Figure 1 below, a histopathological cross-section of a TNBC tumour is shown in comparison to a BC tumour which has all three biomarkers that are typically not present in TNBC patients.* ***Figure 1:** Side-by-side comparison of a TNBC tumour vs a non-TNBC invasive BC tumour. The brown stains on the right-hand side (RHS) indicate the presence of ER, PR, and HER2, which are not present on the left-hand side (LHS). HER2 is a typical biomarker in BC, which is why it's so heavily stained in tumour 2 (Adisa et al., 2012).* ***TNBC has multiple biomarkers which are explored in order to verify a diagnosis that doesn't rely on ER, PR or HER2. Though there are many hotspot mutations, it's been proven that TP53, PIK3CA, and the BRCA1, and BRCA2 panel are areas of interest.*** ***BRCA1 and BRCA2 mutations are valuable biomarkers for TNBC, explicitly for their response to treatment. A study conducted in 2022 explored the BRCA panel and confirmed that the pathological complete response (pCR) is much higher for patients with a mutation in their BRCA gene, after being treated with neoadjuvant chemotherapy (NACT). (Pavese et al., 2022)*** ***TP53 is one of the most important tumour suppressor genes but also plays a detrimental role in tumour development when the gene is mutated. The evolution of this gene suggests that P53 has null alleles which relate to longevity, but this leads to an increase in the risk of cancer, and hence, the regular function of the gene*** (Voskarides & Giannopoulou, 2023)***.*** ***PIK3CA is the gene which regulates cell proliferation and apoptosis. This is especially a topic of interest when researching the effects that PIK3CA has on the cell cycle, and hence, mutations in this gene have been shown to suppress the natural course of apoptosis concerning TNBC tumour cells.*** ***Experimental data conducted in other studies have concluded that immunohistochemical analysis and western blotting attested in mice, have shown that apoptotic markers (such as Caspase 3) express different levels of proteins in mutated PIK3CA (Hu et al., 2021).*** *Upon examination of the secondary data, many questions arise concerning the statistics that are initially seen, such as;* *How many patients have a BRCA panel that also has metastasis? Are there any patients who have metastasis and no BRCA panel? If so, what are other potential hot-spot mutations?* *Is there a correlation between young and older patients when it comes to their diagnosis? Do patients with different hot-spot mutations have a better or worse prognosis?* *Is there any data that should be added to this specific set that may lead to further studies?* *These are all important questions that can be answered through analysing these 30 patients. **Multiple recent studies have demonstrated that patients develop pCR after the latest completed chemotherapies, despite the known aggressiveness of TNBC.*** ***Furthermore, it has been clinically proven that when a patient develops a metastasis as a result of TNBC, the results are still fatally harmful*** (Derakhshan & Reis-Filho, 2021)***.*** 2. ***Methods*** ***The data set investigated in this paper is secondary data, provided by Technological University Dublin.*** ***In accordance with the privacy, health and safety regulations implemented by the university, the primary methods used to source this data is unknown.*** *All data has been analysed in the Microsoft software program, Excel.* *The types of data analysis performed in this paper are as follows;* *Table 1 manual organisation. Table 2 T-test 1,2 and 2,2.* *Figure 2* and *3 pie chart. Table 3* manual organisation and range with percentage. *Table 4* manual organisation of heat map with conditional formatting setting. *Table 5* Anova single factor, and *Table 6* Chi square analysis. 3. ***Results*** 1. ***Secondary Data*** ***Table 1: Secondary data table of 30 patient samples diagnosed with TNBC, and their corresponding prognosis.*** *Each patient with a metastasis has a date of diagnosis ranging between 2006 - 2007, and a year of death ranging between **2007 -- 2013, with the exception of patients 7, 9,13, and 17 who have no known metastasis but have deceased. There are alternative hot-spot mutations to TP53, PIK3CA, and the BRCA1 / BRCA2 panel which can be seen in Table 1 above, in the mutated gene section. Other key mutated genes include; AKT1, KDR, ATM, and KIT, which are present in most patients. The only exception is patient 29 (age 42), which has a mutation in the E-Cadherin (CDH1) gene (refer to section 4.4 KIT and CDH1 in the discussion section).*** ***3.2 Age and Metastasis*** ***Table 2 of the data represents the patient\'s age concerning their metastatic diagnosis. The graph shown on the RHS in Table 2 describes the number of patients who have metastasis versus those who do not. Although the number of patients who do not have metastasis is much higher than the opposing statistic, the error bars are a crucial part of avoiding bias.*** ***Table 2: Graph of the correlation between age and metastasis.*** ***To prove this, two T-tests are applied where the p.value is a standard value, which states that any value under (\) 0.05 is not significant. T-tests (1,2 and 2,2 ended) have been performed to find a value for the collective data (0.312) and for metastasis only (0.156). The results prove that there is no considerable correlation between a patient\'s age and metastasis, which suggests that age does not play a role in TNBC diagnosis; hence, genetic mutations can occur at any age.*** 3. ***Tumour size, Age, and Metastasis*** *Figure 2 on the RHS represents the percentage of patients within each age category, ranging between 21 and 71^+^ years.* *This set shows that there are 2 patients (i.e. 6% of the total number of patients) under the age of 31, 8 patients (27%) between 31 and 40 years, 6 patients (20%) between 41 and 50 years, 5 patients (17%) between 51 and 60 years, 5 patients (17%) between 61 and 70 years, and 4 patients (13%) which are 71^+^ years of age.* *Referring to the graphs in Table 2, this pie chart denotes the range of ages within this study and further proves the hypothesis that age does not play a role in TNBC.* ***Figure 2:** Percentage of patients within each age category, concerning the study at hand.* ***Table 3**: Condensed table of data represented by Table 1; an investigation of tumour size concerning the patient, age, and metastasis status.* *Figure 3 displays a visual aid of the total percentage of patients within each tumour size category, relating to the data presented in Table 3.* ***Figure 3:** Percentage of tumour metastasis within each tumour size category.* 4. ***Heat Map And Anova*** ***The heat map in Table 4 describes the investigative data analysis of each patient and their corresponding mutated genes. The heat map below describes the number of mutated genes each patient has.*** ***For example, patient 15 has had 4 mutated genes in TP53, 3 mutated genes in KDR and ATM, and 30 other mutated genes that are not strictly related to the hot-spot mutations investigated in this paper.*** ***The numbers range from no gene mutations to 30 different gene mutations per patient, which darken in colour as the number increases.*** ***To investigate this data, an Anova - Single Factor test is performed to further understand this data.*** ***Table 4:** Heat map of 30 patient samples and the number of prevalence within each hotspot gene mutation.* ***Table 5: Anova -- Single Factor data analysis of the patient samples described in Table 4.*** ***The summary in Table 5 describes the data set categorised into 10 columns, where the number of patient metastasis is calculated as well as the studied gene mutations.*** ***The average of the variance is calculated also and the absolute mean difference is obtained for BRCA1, BRCA2 and TP53, as these are the most heavily prevalent gene mutations throughout this data set.*** ***The source of variation is calculated where the F-value (7.246), P-value (1.65751E^-9^), and F-crit value are the figures of interest. The ANOVA tests states that the F-value is larger than the F-crit value, meaning that the data is significant.*** ***A further test to calculate the Q-critical value can be performed to explicitly determine this data is true, however; this is sufficient for this paper.*** 5. ***Chi-square*** ***Despite the many mutations which have been detected, two mutations in particular are further investigated due to their reoccurrences in gene mutations; PIK3CA (E707K), and KDR (Q472H). A Chi-square is performed for each gene mutation to further analyse the data. The patient details described in Table 6 separate the patient data into ranges of counted mutations, such that 21 patients had between 1 to 3 mutations (e.g., patients 5, and 6 referred in Table 4), 6 patients had between 4 and 10 mutations (e.g., patient 1 and 11), etc.*** ***Table 6: Chi-square data analysis performed for the genetic mutations found for PIK3CA (E707k) and KDR (Q427H).*** ***The observed (O) table sorts the patient data into the total number of mutations and total number of patients without mutations, whether they have a metastasis or not, patients with the specific genetic mutation in question (either E707K or Q472H), and the number of patients with a metastasis holding the corresponding genetic mutation.*** ***The expected (E) table finds the sum of the (O) table, and the analysis table below (E), describes the overall analysis of all tables. From this, the x^2^ value represents the Chi-squared value, df represents the degrees of freedom, the p-value and the Chi-Square p-value which represents the limit which proves the data to be significant or insignificant. Following this investigation, it was concluded that the data findings are of significance, as the p-value and Chi-Square value are much below the hypothesis p-value of 0.05.*** 3. ***Discussion*** ***4.1 BRCA1 and BRCA2*** ***TNBC has many mutational hot spots that can be investigated for further analysis when it comes to individual patient treatment.*** ***From the data represented in Table 1, the hot-spot mutations can be seen to range from one mutation to three or more mutations; all of which play an important role in the cell cycle, tumour growth, pathogenicity and metastasis where applicable.*** ***The next observable data seen is that all patients with metastasis have deceased, and most patients have a positive BRCA1 and BRCA2 screening.*** ***It is important to note that the motive for patients with no identifiable BRCA screening is unknown. It is hypothesised that the BRCA panel test may have been unnecessary, or test results could have come back with no mutations.*** ***9 out of 12 patients have metastasis, 12 out of the 30 patients have deceased as a result of these gene mutations, and patient 15 has no metastasis/has not deceased, however patient 17 in contrast has 4 mutated genes in BRCA1, and 1 mutated gene in BRCA2 and TP53 with no metastasis but has diseased.*** ***4.2 PIKCA (E707K) and KDR (Q472H)*** ***PIK3CA, according to the detailed secondary data, which is not provided in this paper, has a genetic mutation in the gene E707K. This mutation is an unusual hotspot mutation, as there is very little information on databases concerning this mutation but it must be taken into account that there are 11 out of 30 patients who have a mutated E707K gene.*** ***A study has found however, that when tested in mice, the E707K genetic mutation is known to arise in breast and parotid glands and can be used to identify populations which have drug-tolerant cancerous cells (Ishida et al., 2017).*** ***When identifying the KDR mutated gene Q472H, another study found that by investigating other cancer types such as melanoma, Q472H is associated with the Vascular Endothelial Growth Factor (VEGF) secretion and increased tumour vascular density, which is typically associated with later stages of cancer (Phadnis et al., 2023).*** ***The Chi-square presented in Table 6 for E707K could be further studied to identify why this specific mutation has been found to have drug-tolerance properties.*** ***The Chi-square associated with Q472H could help further investigate vascular density activity by studying the prevalence in later-stage cancers. This could also hugely impact a patient\'s reaction to certain treatments, and hypothetically why so many patients presenting with these two mutations, are deceased.*** ***4.3 AKT1 and ATM*** ***Referring back to the list of mutations that are not strictly related to TP53, PIK3CA or the BRCA panel described in Table 1 of the results section, AKT1 is the gene mutation that is most prevalent in combination with TP53, PIK3CA, and other mutated genes.*** ***Patient 22 is the only patient who has a mutation of AKT1 in singularity and has decreased. AKT1 is a kinase family which is responsible for the proliferation and improved survival of the cell. It was revealed that a gain or loss in activity which activates the AKT1 pathway, relates to the development and evolution of BC.*** ***A study has found that even with extensive investigations, it is still unknown how this particular pathway impacts the genetic mutations, only that it does, and hence; finding this genetic mutation in combination with other gene mutations in Table 1, is indicative of proliferation of the tumour sizes and metastatic status (George et al., 2022).*** ***Studies on the ATM gene have discovered that the mutated version of this gene is strictly related to the cell cycle, telomeric maintenance, oxidative stress, apoptosis, and breast cancer proliferation (Stucci et al., 2021).*** ***There are 5 instances (refer to Table 1) where ATM has occurred, but specifically for patient 9, there is no known metastasis present, a non-applicable clinical variance, and a T3 tumour size which have led to the patient decease.*** ***4.4 KIT and CDH1*** ***The KIT gene is also referred to as the c-KIT which when mutated, can lead to uncontrolled proliferation via kinase activation.*** ***A study demonstrates their findings of how c-KIT plays the role of triggering cell death, however, when c-KIT interacts with the ligand known as the Stem Cell Factor (SCF), this activity is no longer true (Wang et al., 2018).*** ***There are 2 instances where KIT is a genetic mutation for patients diagnosed with TNBC in the data set. Patient 9 which holds no metastasis, and patient 16 which does have metastasis;*** ***Both diseases show that the mutation of KIT is in combination with a mutation of TP53 in both instances. This could further be investigated to test if KIT has an enhanced ability to be fatal when in combination with another genetic mutation.*** ***CHD1 is the exception of the gene mutations of this investigative study. CHD1 is typically related to Hereditary Diffuse Gastric Cancer (HDGC) but has been found to also identify with instances of BC.*** ***A study announced that there is a 42% risk of BC in females, concerning the data provided by that study (Hansford et al., 2015). Patient 29, despite having a total of 32 found genetic mutations (13 in BRCA1, 18 in BRCA2 and the CHD1 mutation), did not have any metastasis and did not decease.*** ***Conclusion*** Throughout this investigative data analysis paper, genetic mutations that occur in TP53, PIK3CA, BRCA1 and BRCA2, ATM, ATK, KIT, and CDH1 have been investigated and discussed. This paper has found that the highest mutations occur in the BRCA1 and BRCA2 panels as well as in TP53 and PIK3CA. Although these are not the only mutational hotspots, the other mutations also play a major role in tumour proliferation, the cell cycle, patient prognosis, metastasis, potential treatment and fatalities. In conclusion, there is no correlation between a patient\'s age and their prognosis, and the tumour size is not strictly related to the metastatic diagnosis. Findings suggest that the bigger the tumour size, the more likely a patient is to develop metastasis. 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