{"id":60953,"date":"2024-09-30T10:28:22","date_gmt":"2024-09-30T10:28:22","guid":{"rendered":"https:\/\/biomedpharmajournal.org\/?p=60953"},"modified":"2024-10-09T18:43:23","modified_gmt":"2024-10-09T18:43:23","slug":"evaluation-of-ki67-biomarker-as-a-prognostic-marker-in-breast-invasive-ductal-carcinoma-in-khartoum-state-in-sudan","status":"publish","type":"post","link":"https:\/\/biomedpharmajournal.org\/staging\/vol17no3\/evaluation-of-ki67-biomarker-as-a-prognostic-marker-in-breast-invasive-ductal-carcinoma-in-khartoum-state-in-sudan\/","title":{"rendered":"Evaluation of Ki67 Biomarker as a Prognostic Marker in Breast Invasive Ductal Carcinoma in Khartoum State in Sudan"},"content":{"rendered":"\n

Introduction<\/strong><\/p>\n\n\n\n

Breast\ncancer is the most common malignancy in women worldwide and the primary cause\nof cancer-related deaths. Breast cancer is becoming an increasingly critical concern in low- and\nmiddle-income countries (LMICs), where incidence rates have risen by up to 5%\nevery year 1<\/sup>. Hulka and colleagues defined biological markers as cellular,\nbiochemical, or molecular changes in biological media. They are used for\ndisease prediction, etiology, diagnosis, progression, regression, and treatment\noutcome, and have expanded to include biological properties 2<\/sup>.  Tissue microarrays (TMAs) are\ncreated by extracting punches from paraffin-embedded tissue blocks and\ntransferring them to a positionally encoded array. While not used for clinical\ndiagnosis, they offer advantages over traditional histological sections,\nallowing hundreds of analyses per microarray. 3 <\/sup><\/p>\n\n\n\n

The process of multiplying a cell is known as cell proliferation, and it is characterized by the equilibrium between cell divisions and cell loss via differentiation or death. Tumors exhibit increased cell division.4<\/sup><\/p>\n\n\n\n

Ki-67\nexpression changes during the cell cycle, raising concerns that cycling cells\nmay be misclassified as resting cells. According to the data as a whole,\nKi-67 levels are low throughout the G1 and early S phases and progressively\nrise to a peak during mitosis. Anaphase is the start of a sharp decline in\nexpression 5<\/sup>.<\/p>\n\n\n\n

There is a lot of interest in using cell proliferation indicators to help classify cancers, notably malignant lymphoma, as well as possible indications of therapeutic responsiveness to chemotherapeutic drugs. Two types of antibodies can be utilized successfully on paraffin sections: Ki67 (MIB1) and PNCA. The G1, S, G2, and M phases of the cell cycle are those in which proliferating cells express a nuclear antigen that is recognized by the monoclonal antibody Ki67. G0 cells do not express Ki67 while they are in the resting phase. An extremely labile epitope that is only reliably found in frozen sections or cytological materials is recognized by the Ki67 antibody 6<\/sup>. Newer antibodies have recently been produced against recombinant portions of the Ki67 molecule. MIB1 is a robust reagent for Ki67 expression assessment in breast cancer, enhancing prognostic capabilities 7.<\/sup> It can be used consistently in formalin-fixed paraffin-embedded tissues after microwave antigen retrieval.<\/p>\n\n\n\n

In\nSudan, the incidence of breast cancer has been raising to be the most common\ncancer 8<\/sup>.The objective of this investigation was to ascertain the\nproliferative index level utilizing the immunohistochemical marker Ki67 in connection\nwith the histological grade of breast cancer. Additionally, we sought to\ninvestigate the correlation between the level of Ki67 marker expression and the\nhistological grade of breast cancer, as well as the relationship between\nproliferative marker Ki67 intensity and patient age and IHC score.<\/p>\n\n\n\n

Materials and Methods<\/strong><\/p>\n\n\n\n

This\nis a retrospective cross-sectional laboratory investigation conducted from June\n2018 to July 2019 at the Alrahma Medical Laboratory in Khartoum, Sudan. In\n2018, Breast\ncancer tissues were histologically examined using hematoxylin and eosin-stained\nslides, then Tissue Microarrays technique (TMAs) and Ki67 monoclonal antibody\nstained for microscopical examination.<\/p>\n\n\n\n

 This study included only invasive ductal\ncarcinoma cases with complete information about age, diagnosis, and\nhistological grade.  Ethical\nconsiderations for Alrahma Medical Laboratory in Khartoum.  Data was acquired from a master sheet of\npatient data, which included age and histological grade, with the type of\ncancer previously classified as invasive ductal carcinoma (IDC).\nThe\nprocedure involved a surgeon taking a biopsy or breast resection specimen,\ndepositing it in formalin, and analyzing it to select and cut tissue sections.<\/p>\n\n\n\n

Two\ntissue blocks were stained and cut into sections for Hematoxylin and Eosin\nstain and immunohistochemistry techniques, mounted on glass slides and backed\nat 60 C for six hours.<\/p>\n\n\n\n

 Manual Tissue Arrayer<\/strong><\/p>\n\n\n\n

A paraffin block was created by pouring liquid paraffin into a mold, covered with a tissue cassette, and then examined for bubbles or holes. Extra paraffin from plastic cassette was used to identify donor tissue blocks’ regions of interest, determine ideal TMA architecture, and create a TMA block summary. The TMA 1 arrayer’s two punches were aligned on an empty paraffin block, ensuring proper alignment and similar centers in the circular indents they create. Tighten the adjustment nut to the required depth within the Paraffin block, typically 0.5-1 mm above the plastic tissue cassette base.<\/p>\n\n\n\n

The\nprocess involved creating holes in the array’s first position, adjusting\nmicrometers, releasing tissue punches, discarding paraffin wax, and moving the\nbigger punch into the sampling position, removing the donor block bridge. <\/sup><\/p>\n\n\n\n

The donor block was manually held on the donor block bridge, and the tissue core region was sampled beneath the sample punch, which was pushed downward. The tissue microarray (TMA) is created by creating a gap of 0.8-1 mm between sample centers. The TMA is then sectioned using an adhesive-side-down tape window, a microtome blade, and a 5-micrometer slice. The tissue is then placed on a microscopic slide and cured using a UV lamp. The slide was placed in TPC SOLVENT for 3 minutes, then a fresh section was cut for H&E staining, Ki67 staining, and immunohistochemistry (IHC) was performed.<\/p>\n\n\n\n

Results<\/strong><\/p>\n\n\n\n

Breast cancer is the\nmost prevalent cancer in women worldwide, and it has high Ki67 expression. 35\ntissue samples previously diagnosed with aggressive breast ductal carcinoma were\nused in this retrospective study to evaluate the expression of Ki67\nproliferative marker as a prognostic marker in invasive ductal carcinoma using\nmanual tissue microarrays (MTMA). The patients were between the ages of 31 and\n71. The age group that was most prevalent was 50-60 years old (31.4%) (11\/35),\nfollowed by 30- 40 years old patients (10\/35) 28.6% (10\/35) and 40 to 50 years\nold patients (10\/35) 28.6%, then 60-70 years old (3\/35) 8.6%, and finally 70 to\n80 years old (1\/35) 2.9%, as shown in Figure (1).<\/p>\n\n\n\n

The study’s findings\nrevealed that the bulk of samples were grade three (77.1%, 27\/35) and grade two\n(22.9%, 8\/35) with no grade one samples Figure\n(2). \nThe study found that the bulk of IHC positive results in the nucleus\nwere 94.3% (33\/35) with only two negative results accounting for 5.7% (2\/35),\nsee figure (3). The study found that the majority of TMA scores were\n(+) 34.3% (12\/30), followed by (++) 31.4% (11\/35), (+++) 25.7% (9\/35) and only\none sample had (++++) 2.9% (1\/35) and two negative findings 5.7% (2\/35) , see figure\n(4). The investigation revealed that\nthere is no link between histological grade and patient age (P-value = 0.683)\nand a very weak correlation (0.065) (tables 01). The study found a medium\ncorrelation between score and patient age (P-value = 0.047. Tables (2) and (3)\nshow a substantial correlation (P-value = 0.47) between patient age and score.<\/p>\n\n\n\n\n\n
\"\"<\/td>\n\n

Figure<\/strong> 1: Distribution of patients included in the study according to their Age<\/strong><\/p>\n

<\/p>\n

Click here to view Figure<\/a><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n\n
\"\"<\/td>\n\n

Figure<\/strong> 2: Distribution of samples according to their Histological Grade<\/strong><\/p>\n

<\/p>\n

Click here to view Figure<\/a><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n\n
\"\"<\/td>\n\n

Figure<\/strong> 3: Distribution of samples according to their IHC<\/strong><\/p>\n

<\/p>\n

Click here to view Figure<\/a><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n\n
\"\"<\/td>\n\n

Figure<\/strong> 4: Distribution of samples according to their IHC Score.<\/strong><\/p>\n

<\/p>\n

Click here to view Figure<\/a><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n\n\n
\n

Chi-Square<\/strong><\/p>\n<\/td>\n

\n

Correlation<\/strong><\/p>\n<\/td>\n

\n

P.value<\/strong><\/p>\n<\/td>\n<\/tr>\n

\n

1.496<\/p>\n<\/td>\n

\n

-.065<\/p>\n<\/td>\n

\n

.683<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n

Table 2: The relationship between IHC and patient\u2019s age<\/strong><\/p>\n\n\n\n\n\n\n
\n

Chi-Square<\/strong><\/p>\n<\/td>\n

\n

Correlation<\/strong><\/p>\n<\/td>\n

\n

P.value<\/strong><\/p>\n<\/td>\n<\/tr>\n

\n

3.845<\/p>\n<\/td>\n

\n

-.282<\/p>\n<\/td>\n

\n

.279<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

 <\/p>\n\n\n

Table 3: The relationship between Score and patient\u2019s age<\/strong><\/p>\n\n\n\n\n\n\n
\n

Chi-Square<\/strong><\/p>\n<\/td>\n

\n

Correlation<\/strong><\/p>\n<\/td>\n

\n

P.value<\/strong><\/p>\n<\/td>\n<\/tr>\n

\n

2.994<\/p>\n<\/td>\n

\n

.461<\/p>\n<\/td>\n

\n

.047<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

 <\/p>\n\n\n

Table 4: The relationship between Score and TMA<\/strong><\/p>\n\n\n\n\n\n\n
\n

Chi-Square<\/strong><\/p>\n<\/td>\n

\n

Correlation<\/strong><\/p>\n<\/td>\n

\n

P. value<\/strong><\/p>\n<\/td>\n<\/tr>\n

\n

35.000<\/p>\n<\/td>\n

\n

.421<\/p>\n<\/td>\n

\n

.000<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

 <\/p>\n\n\n

Table 5: The relationship between Grade and Score<\/strong><\/p>\n\n\n\n\n\n\n
\n

Chi-Square<\/strong><\/p>\n<\/td>\n

\n

Correlation<\/strong><\/p>\n<\/td>\n

\n

P. value<\/strong><\/p>\n<\/td>\n<\/tr>\n

\n

.488<\/p>\n<\/td>\n

\n

.756<\/p>\n<\/td>\n

\n

.087<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

 <\/p>\n\n\n

Discussion<\/strong><\/p>\n\n\n\n

The\nhallmark of cancer is unchecked proliferation. The most widely used method for\nmeasuring tumor growth in breast cancer is the fraction of cells that stain for\nthe nuclear antigen Ki67. <\/p>\n\n\n\n

The current study observed that high\nlevels of Ki67 expression corresponded with a prevalent histological grade,\nwith 77.1% of our samples classified as grade III (Figure 2). This finding\nsupports the study conducted by Dowsett and his team, indicating that higher\nKi67 levels typically correlate with more aggressive forms of breast cancer and\npoorer patient outcomes 9<\/sup>. Specifically, Ki67 expression has been\nshown to be a strong independent prognostic factor in early breast cancer,\nreinforcing its utility in stratifying patient risk 10<\/sup>.<\/p>\n\n\n\n

The current study also found Ki67\npositive in 94.3% of specimens (Figure 3), suggesting that proliferative\nactivity is a key characteristic in the majority of IDC cases. Furthermore, our\nresults indicated a significant correlation between Ki67 scores and patient age\n(P=0.047) (Table 3), hinting at the importance of considering patient\ndemographics when evaluating Ki67 as a prognostic marker. This aspect is\nparticularly relevant given that age is often associated with tumor biology and\npatient response to treatment 11<\/sup>.<\/p>\n\n\n\n

Our study and others have suggested\nthat patients with tumors exhibiting more than 50% proliferation may respond\nfavorably to chemotherapy 12<\/sup>. Conversely, two cases in our study\nwith negative Ki67 results may indicate a better prognosis, potentially\nrepresenting tumors that are not yet fully proliferative or are in earlier\nstages of development.<\/p>\n\n\n\n

Despite its clinical relevance, the\ninterpretation of Ki67 remains complex due to variability in methodologies used\nacross different laboratories. Scholars, including Alco and his team. 13<\/sup>,\nhave noted that discrepancies in Ki67 measurement could arise from variations\nin tissue handling, fixation protocols, and antibody specificity. Additionally,\nthere exists an ongoing debate regarding the establishment of an optimal Ki67\ncut-off value, which varies significantly among studies and populations 14<\/sup>.\nConsequently, the need for standardized protocols and guidelines for Ki67\nevaluation is paramount to ensure consistent and clinically relevant results\nacross settings.<\/p>\n\n\n\n

The integration of Ki67 in\nmultimodal prognostic assessments, alongside established markers such as ER,\nPR, and HER2, is highly recommended. This combined approach enhances the\nprecision of survival predictions and treatment planning for patients with breast\ncancer 15 <\/sup> . In our study, the\ncorrelation between Ki67 scoring and histological grade (P=0.087, Table 5)\nindicates that incorporating multiple parameters may offer more robust insights\ninto patient prognosis.<\/p>\n\n\n\n

The current study evaluating Ki67 as a prognostic marker in breast\ninvasive ductal carcinoma has several limitations, including its retrospective\ndesign and small sample size of only 35 tissue samples, which may affect the\ngeneralizability of findings.<\/p>\n\n\n\n

Conclusion<\/strong><\/p>\n\n\n\n

The\npresent results indicated the significant role of the Ki67 biomarker as a\nprognostic indicator in invasive ductal carcinoma (IDC) of the breast. The\nmajority of cases analyzed demonstrated high levels of Ki67 expression (94.3%),\nwhich correlate with more aggressive tumor behavior and poorer prognostic\noutcomes. Importantly, also findings indicate that there is no significant\nassociation between Ki67 scores and patient age \nsuggesting that age is not a determining factor in the prognostic impact\nof Ki67 . Future work should focus on standardization of Ki-67\nassessment and specific-cation of its role treatment protocol. <\/p>\n\n\n\n

Acknowledgment<\/strong><\/p>\n\n\n\n

The author wishes to express gratitude to\nAlrahma Medical Laboratory in Khartoum, Sudan, for supporting the research\nwork. Special thanks to the laboratory staff for their assistance and\ncooperation during the study. The author is also deeply appreciative of the\nresources and facilities made available, which significantly contributed to the\nsuccess of this research.<\/p>\n\n\n\n

Conflict of Interest<\/strong><\/p>\n\n\n\n

The authors do not have any conflict of\ninterest <\/p>\n\n\n\n

Funding Sources<\/strong><\/p>\n\n\n\n

The author(s) received no financial support for the research, authorship, and\/or publication of this article.<\/p>\n\n\n\n

Data Availability Statement<\/strong><\/p>\n\n\n\n

This statement does not apply to this article.<\/p>\n\n\n\n

Ethics Statement<\/strong><\/p>\n\n\n\n

This research did not involve human participants, animal subjects, or any material that requires ethical approval.<\/p>\n\n\n\n

Informed Consent Statement<\/strong><\/p>\n\n\n\n

This study did not involve human participants, and therefore, informed consent was not required.<\/p>\n\n\n\n

References<\/strong><\/p>\n\n\n\n

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