Because cancer cells grow and divide rapidly, Ki is sometimes considered a good marker of proliferation tumor marker , helping your healthcare provider follow the progress of cancer. However, its use in breast cancer is controversial.
The Ki test may be performed on a sample of breast cancer tissue to help predict the tumor's aggressiveness. The test, which is performed and interpreted by a doctor called a pathologist, measures the level of Ki expression in the cancer cells through a staining process. While the Ki proliferation marker test is increasingly ordered by healthcare providers, its overall benefit, specifically when it comes to making decisions about treatment, is not certain.
Your healthcare provider may order the Ki test as a way to measure how quickly your breast cancers cells are dividing and forming new cells. The test does this by using an antibody called MIB1 on tissue samples. The more cells MIB1 attaches to, the more likely tumor cells are to grow and divide rapidly. Your Ki score may help you and your healthcare provider determine your cancer prognosis or your chance of recovery. Some studies have found that tumors with higher levels of Ki may have a worse prognosis than tumors with lower levels.
On a more positive note, research has also found that tumors with a high level of Ki may respond particularly well to chemotherapy. Since chemotherapy attacks all rapidly growing cells including "normal cells" such as hair follicles , tumors that are more aggressive divide more rapidly may respond particularly well to these regimens. This is, in fact, why some very aggressive cancers such as acute lymphocytic leukemia that used to be quickly fatal now can often be cured with chemotherapy.
Healthcare providers should not use Ki protein levels in tumor cells to make decisions about treatments after surgery. Among breast cancers that are hormone-positive, there are two distinct subtypes that have different prognoses and may respond differently to treatment. Ki has been used as an adjunct in separating tumors into these two categories, though MCM2 appears to be a promising alternative.
Despite their molecular distinctions, the treatment of luminal A and luminal B tumors is the same. A "high" score means that the breast tumor is more likely to be aggressive and spread quickly. Even so, not all healthcare providers order the Ki test, so don't be alarmed if it's not on your pathology report. In addition, it's important to note that other tests are done to assess your breast tumor. Significance of p53 and ki expression in prostate cancer.
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Short-term changes in Ki during neoadjuvant treatment of primary breast cancer with anastrozole or tamoxifen alone or combined correlate with recurrence-free survival. The different cut-off values used were those of the authors range: 3. Threshold definitions were mean or median values, the best cut-off value or an established arbitrary value. Regarding OS patients , of all 35 studies, subgroup analysis was possible in nine studies with node-negative patients patients Jensen et al, ; Weikel et al, ; Bevilacqua et al, ; Brown et al, ; Domagala et al, ; Fresno et al, ; Rudolph et al, a ; Trihia et al, ; Erdem et al, , in four with node-positive patients patients Weikel et al, ; Domagala et al, ; Gonzalez et al, ; Trihia et al, and in two that included only untreated patients node-negative and node-positive patients Pinder et al, ; Bevilacqua et al, For the untreated patients subgroup analysis, worse DFS was found in all node-negative patients HR 2.
Results of the meta-analysis with all evaluable studies for DFS. The squared size is proportional to the number of patients included in each study. Results of the meta-analysis with all evaluable studies for OS. The necessity to exclude some studies due to a lack of results for aggregating the results is a well-known important problem when conducting a meta-analysis, because the excluded studies show often a smaller effect compared to the studies published with full details and evaluable for the meta-analysis.
To assess the impact of bias related to the unevaluable studies that might lead to an overestimation of the effect , we performed an analysis on the overall patient populations including both evaluable and unevaluable studies.
For papers reporting only HR estimates obtained in multivariate analyses, we used this HR estimate together with its variance. For those with uncertainties related to the number of events and then the variance of the HR estimate, we made rough approximation of the variance. Finally, for the studies where no useful information could be retrieved from the publication, we considered that the HR estimate was 1 i.
Even by carrying out this sensitivity analysis, we still observe a significant pejorative impact of Ki positivity on DFS HR 1. The present meta-analysis confirms that high Ki expression in patients with early BC confers worse prognosis in the overall population and quantifies its prognostic univariate impact.
Further, it was also shown in subgroup analyses for node-negative, node-positive and untreated patients. Prognostic markers may be defined as those markers that are associated with some clinical outcomes, typically a time-to-event outcome such as OS or DFS, independently of any treatment or intervention. The best setting to apply this concept is in untreated populations, which helps identifying the so-called pure prognostic marker.
Prognostic markers may also be used to aid the decision-making process for adjuvant therapy, for example, they may be used as decision aids in determining whether a patient should receive adjuvant chemotherapy or how aggressive that therapy should be McShane et al, As a predictive marker, very few trials of primary systemic therapy, mostly retrospective and with conflicting results have been published Colozza et al, , and therefore we felt that the assessment of the predictive role of Ki was out of scope for this meta-analysis.
Our meta-analysis was carried out using literature published results, and we therefore acknowledge some limitations of our approach which is, however, much less expensive than a meta-analysis using individual patients data. The language selection could favour positive studies, following the assumption that they are more often published in English, whereas the negative ones tend to be published more often in local journals using the author's native languages Egger et al, However, we did not identify many papers published in a national language Italian, Russian, Serbian, German Lelle, ; Topic et al, ; Kushlinskii et al, ; Costarelli et al, Another possible source of confusion is the use of the same cohort of patients in different publications, although studies that were clearly based on the analysis of the same patient cohorts were excluded in this meta-analysis.
Some authors consider meta-analyses using individual data to be the gold standard evidence Stewart and Parmar, ; Oxman et al, This approach is normally considered to be a new study that takes into account all performed studies on the topic, published or not, and that requires an individual data update by the investigators; it is thus much more time consuming, complex and costly. In a comparison between a meta-analysis based on individual patient data and one based on extracted data, the overall duration for the former was found to be 1—5 years while for the latter it is only 1—5 months.
Therefore, a meta-analysis on published literature is worthwhile and, especially in a situation, as here, it is very unlikely to find the resources to conduct a meta-analysis based on the individual data.
The method used for extrapolating HR might be a source of some variability in the HR estimates. When no other useful information was available, we extrapolated the HR from the survival curves using several time points during follow-up for reading the corresponding survival rates, assuming that censored observations were uniformly distributed. The estimation of survival rates based on the graphical representation of the survival curves was performed independently by three of the authors and we compared our HR estimate and its statistical significance with the results published in each individual trial.
We did not identify any major contradiction between our results and the results available in the papers. The adverse impact of Ki positivity on both OS and DFS was observed in the overall population as well as in the subgroups node-negative and node-positive patients. Significant heterogeneity was detected when considering the whole population and node-negative patients. It is not considered appropriate to define a single measure i. HR associated with Ki positivity in this case from studies with inherent dissimilarities.
The observed disparity among the conclusions of different studies, responsible for the observed heterogeneity, can be quantified by applying quality scores to the selected studies included in the meta-analysis. However, these scores do not always explain the observed results Greenland, In this case, the methodological characteristics of each study must be taken into consideration.
In , Cattoretti et al reported better success in staining Ki in paraffin-embedded samples after the new antibodies anti-MIB-1 and anti-MIB-3 had been developed. Although several antibodies are now commercially available to stain Ki, anti-MIB-1 is the most frequently used in recent studies Urruticoechea et al, In our meta-analysis, antibodies other than anti-MIB-1 and anti-Ki were included, such as anti-Ki-S5 Rudolph et al, a ; Esteva et al, and anti-Ki-S11 Rudolph et al, b , albeit representing only a minority of the cases.
Moreover, Ki expression is usually estimated as the percentage of tumour cells positively stained by the antibody, with nuclear staining being the most common criteria of positivity. The use of different antibodies and scoring protocols without a standard minimum number of cells to be counted may account for some of the differences between the studies. A further limitation of our meta-analysis is that it assesses only the univariate prognostic value of Ki So, we cannot infer from our meta-analysis that Ki is an independent factor; the answer to that question should come from a prospective study it is likely that a meta-analysis of individual data would not solve the question as the intersection of the sets of covariates available in the individual studies is most probably very small.
To better clarify the prognostic role of ER status, Sotiriou et al used gene array profiling to explore the implications of the joint distribution of ER status and gene expression grade index GGI to predict clinical outcome. This means that GGI adds additional prognostic information when the ER status is known, whereas the opposite is not true.
Unfortunately, due to the lack of information in the published studies used in our study, an analysis of the impact of Ki expression on the ER-negative and ER-positive subpopulations and grade, which are well-known risk factor associated with worse outcome, was not possible.
Despite years of research and hundreds of reports of tumour markers in oncology, the number of markers that have emerged as clinically useful is quite small. The guidelines contain 20 recommendations derived from studies on tumour markers and regarding study design, methods of statistical analysis, preplanned hypotheses, patient and specimen characteristics, and assay methods.
The widespread use of published guidelines for analytical methods and the reporting of results would greatly facilitate the development of alternative analyses and meta-analyses Alonzo, ; McShane et al, Despite some limitations, this meta-analysis supports the prognostic role of Ki in early BC, by showing a significant association between its expression and the risk of recurrence and death in all populations considered and for both outcomes, DFS and OS.
Had the proposed REMARK guidelines been employed in all the studies selected for this meta-analysis and had all necessary information been available, our literature-based meta-analysis would better characterise the role of Ki as prognostic marker.
This paper was modified 12 months after initial publication to switch to Creative Commons licence terms, as noted at publication. Alonzo TA Standards for reporting prognostic tumor marker studies.
J Clin Oncol 23 : — PubMed Google Scholar. Gynecol Oncol 57 : 96— Breast Cancer Res Treat 37 : — J Pathol : 25— Breast Cancer Res Treat 71 : — The most significant obstacles in the use of siRNAs are efficient uptake and long-term stability ZDKi67 induces silencing of the Ki gene, allowing for efficient tumor-specific viral replication and inducing the apoptosis of tumor cells in vitro and in nude mice Furthermore, the microinjection of antibodies directed against the Ki was shown to result in a decreased rate of cell division , In this technique, the nuclear localization presents a major hurdle, due to the need for intracellular and intranuclear delivery of targeting and therapeutic moieties.
Zhang et al used a liposomally encapsulated construct to design photo immunoconjugate-encapsulating liposomes PICELs. Non-cationic PICELs are particularly useful for the subcellular delivery of mAbs and provide multi-functional constructs for imaging and therapy. In summary, due to its ubiquitous expression in all proliferating cells and the prognostic value of the Ki index in many cancers, pKi is an potentially attractive therapeutic target in cancer, and strategies that inactivate pKi are a promising anti-proliferative approach, with potentially broad applicability in cancer treatment Hence, targeting pathways and molecular markers implicated in cancer cell growth is a promising avenue for the development of effective therapies.
As a proliferation marker to measure the growth fraction of cells in human tumors, the expression of Ki67 is strongly associated with cell proliferation and is widely used in routine pathology. Based on the studies presented here, Ki67 may be a promising molecular candidate for the diagnosis and treatment of a wide range of malignancies. J Cell Physiol. Shirendeb U, Hishikawa Y, Moriyama S, et al: Human papillomavirus infection and its possible correlation with p63 expression in cervical cancer in Japan, Mongolia, and Myanmar.
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