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Prognostic significance of the kinesin superfamily in breast cancer: A systematic review & meta-analysis
For correspondence: Dr Showket Hussain, Department of Cellular & Molecular Diagnostics, ICMR – National Institute of Cancer Prevention and Research, Noida 201 301, Uttar Pradesh, India e-mail: showket.hussain@gov.in
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Received: ,
Accepted: ,
Abstract
Background & objectives
Kinesin superfamily proteins (KIFs), essential motor proteins involved in processes like mitosis and intracellular transport, have emerged as critical players in breast cancer (BC) progression. Recent studies highlight their potential as prognostic biomarkers and therapeutic targets. This research explores the association between the expression of KIFs and survival outcomes, including overall survival (OS), recurrence-free survival (RFS), and distant metastasis-free survival (DMFS).
Methods
In this study, we carried out a meta-analysis as per the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A thorough literature search was conducted using the PubMed and ScienceDirect databases, covering the period from June 1996 to October 2024. Hazard ratios (HRs) and their corresponding 95 per cent confidence intervals (CIs) were extracted from eligible studies and analysed using the RevMan software.
Results
Initially, we screened 220 articles for this systematic review, from which 11 studies met the inclusion criteria for the meta-analysis. In our analysis, we have observed that elevated KIFs levels were associated with poor OS (HR=1.77 with 95% CI=1.58-1.98 and P<0.00001), RFS (HR=1.40, 95% CI=1.31-1.49, P<0.00001), and DMFS (HR=1.72, 95% CI=1.49-1.99, P<0.00001). These findings suggest that increased expression of kinesin family members contributes to reduced survival rates and increases the risks of recurrence and metastasis in BC patients.
Interpretation & conclusions
Our study highlights the potential of kinensin family members as prognostic biomarkers for BC progression, providing insights that may help in clinical decision-making and patient management.
Keywords
Breast cancer
kinesin superfamily
meta-analysis
prognosis
survival rate
Worldwide, breast cancer (BC) is the most commonly occurring carcinoma, followed by that of lung, colorectal and cervix uteri1. A total of 2.3 million new cases and 6,69,846 deaths were reported globally in BC in 20221. In the same year, 14,13,316 new cases of BC and 9,16,827 deaths were reported from India1. The data from the Indian Council of Medical Research (ICMR)-National Cancer Registry Programme show that Hyderabad city has the highest prevalence rate of BC in India2. The challenges in managing heterogeneous malignancy in BC are due to its aggressive nature and the presence of multiple issues like chemo-resistance, radio-resistance, and resistance towards hormonal therapy and targeted therapy1.
Early diagnosis, coupled with effective treatment, is a highly effective approach for BC management. BC pathogenesis is influenced by a category of proteins known as the kinesin superfamily members (KIFs). Only a few studies have investigated the prognostic role of kinesin superfamily members in BCs; however, data specific to BC remain scattered, and no comprehensive meta-analysis has been done for survival for all kinesin superfamily members. The present systematic review and meta-analysis addresses this gap by consolidating existing evidence on kinesin superfamily members expression and quantitatively evaluating their associations with BC survival outcomes.
KIFs are motor proteins actively involved in important cellular functions like cell cycle, mitosis, and meiosis. These proteins were initially isolated from squid tissue and are universally found in all eukaryotes3. KIFs are composed of a globular head (the motor domain) that binds with the microtubules connected with a short, flexible neck linker to the stalk, a long and central stalk that ends in the tail domain (heavy chain), which associates with the light chain. The light chain interacts with the intracellular cargo for transport. There are 45 members in the kinesin family, broadly classified into 14 subfamilies according to their structure, differentiation, and diverse functions (Supplementary Table I)4-44. This family is further categorised into three main groups based on the positions of their motor domains, where 39 members are in the amino-terminal group (N), three are in the middle group (M), and the remaining three are in the carboxy-terminal group (C)45,46. Disruptions in the normal functioning of these members throughout the cell cycle can give rise to unregulated cell proliferation, ultimately contributing to the process of carcinogenesis46. Nevertheless, it is worth noting that the role of different KIFs vary as some KIFs are found to be upregulated in advanced stages of BC, while others are down regulated4,47-50. Several articles suggest the role of kinesin family members in BC; however, information about these members and their functions in breast carcinogesis51 is limited. Understanding the association between the kinesin family and distinct molecular subtypes of BC and their roles in disease progression can offer valuable insights into their clinical and biological significance. In the luminal A subtype, KIF4A, KIF5B, KIF14, and KIF3A are linked to disease progression and therapy resistance52-55. Luminal B tumours showed elevated levels of KIF18A, KIF11, KIF23, and KIF2C, contributing to increased proliferation and resistance to therapy56-59. In HER2-positive BC, the overexpression of KIF2C, KIF20A, KIF23, KIF11, and KIF15 is associated with aggressive tumour growth and activation of the HER2 pathway56. In TNBC, the high expression of KIF20A, KIF14, KIFC1, KIF4A, KIF2C, and KIF18B correlates with enhanced metastasis, poor prognosis, and epithelial-mesenchymal transition (EMT) activation57,58.
The KIFs constitute a varied collection of motor proteins that play crucial roles in intracellular transport, ensuring proper cellular organisation and function4. This study focuses on the entire kinesin family, with an aim to provide a better understanding of these proteins in breast carcinogenesis and the effects of their expression level on overall survival (OS), recurrence-free survival (RFS), and distant metastasis-free survival (DMFS).
Materials & Methods
The current meta-analysis was conducted based on the guidelines of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The details of the checklist are presented in supplementary tables II and III59. The current study was registered in PROSPERO (ID: CRD420251030894).
Search strategy
A comprehensive search conducted from June 1996 till October 2024 using PubMed and Science Direct databases using the search tag ‘kinesin superfamily’ AND ‘breast cancer’ (Search string: (‘kinesins’ [MeSH Terms] OR ‘kinesins’ [All Fields] OR (‘kinesin’ [All Fields] AND ‘superfamily’ [All Fields]) OR ‘kinesin superfamily’ [All Fields]) AND (‘breast neoplasms’ [MeSH Terms] OR (‘breast’ [All Fields] AND ‘neoplasms’ [All Fields]) OR ‘breast neoplasms’ [All Fields] OR (‘breast’ [All Fields] AND ‘cancer’ [All Fields]) OR ‘breast cancer’ [All Fields]). Studies published in the English language were accepted. Additionally, World Health Organization (WHO) databases were searched for BC reports.
Eligibility criteria
Data extraction was independently done through a systematic process involving two authors (S and MA), discussion among the research team, and cross-referencing with source materials. A third author (SS) addressed any unresolved issues and discrepancies. Every disagreement was discussed and resolved after the full text was reviewed. Different types of studies were included, such as case-control investigations, as well as randomised and non-randomised clinical trials. The following criteria were used for study inclusion: (a) publications from June 1996 to October 2024; (b) full text articles published in English language; (c) research investigating the expression of the KIFs in BC; (d) studies reporting survival outcomes using hazard ratio (HR) with 95 per cent confidence interval (CI). Studies were excluded if they focused on cancers other than BC. Furthermore, articles were screened by title and abstract to eliminate ‘reviews’ and ‘meta-analysis’ and others (book chapters, short communication, discussion, encyclopedia, conference abstracts, unpublished theses, and non-English studies). Further, the papers that were not related to BC and KIFs were also omitted; out of these, 11 articles were selected for further meta-analysis on the basis of inclusion criteria.
Data extraction
The articles were compiled using EndNote software (https://endnote.com). Comprehensive data extraction was conducted, encompassing essential information such as author names, design, study type, and publication year, and the elucidation of the connection between KIFs expression levels and outcomes such as OS, RFS, and DMFS. Furthermore, HR, along with their corresponding 95 per cent CI, were systematically collected.
Quality assessment and risk of bias (ROB) analysis
The quality and ROB assessment in all eligible studies were conducted using the Cochrane Collaboration’s Risk of Bias tool (ROB 2.0) within Review Manager software (version 5)59. The following measure was applied to evaluate the ROB rating: ‘random sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcome assessment, incomplete outcome data, selective reporting and other bias,’ shown in supplementary figure 1A. The quality of the assessed studies was calculated based on diagnostic criteria, sample size, assessment of KIFs, and source of data60.
Statistical analysis
The Review Manager 5; RevMan 5 software (London, U.K.) was used for statistical analysis59. We evaluated the strength of the association between the KIFs members with OS, DMFS, and RFS using HR and 95% CI. To evaluate the heterogeneity among the studies, a combination of Chi-squared tests, I2 statistics, and a fixed-effect model was employed. The criteria for significant heterogeneity I2>50 per cent and P<0.001 were used for statistically significant heterogeneity. I2 values were employed to quantify the extent of heterogeneity, where values less than 25 per cent were categorised as low, 25-50 per cent as moderate, and greater than 50 per cent as high.
Results
Selection criteria for the studies
A total of 310 records were retrieved by conducting searches on PubMed and Science Direct databases, following a pre-defined search strategy. After excluding duplicate studies, articles related to other cancers, and articles with insufficient data, only 150 articles underwent initial screening. Six articles were excluded as they were marked reviews or meta-analyses, while 20 were omitted due to a lack of relevance to KIFs; five studies did not report information on BC, and 108 articles were not related to survival analysis for OS, RFS, and DMFS. Among these, 11 results were chosen for inclusion in the meta-analysis. Figure 1 provides an overview of the screening and study selection process, along with explanations for exclusions.
- A flowchart illustrating the process of conducting the literature search and subsequent selection.
Characteristics of included studies
A total of 144 articles were included, of which four were clinical trials and one was a case-control study. Of the 144 articles, 11were included for meta-analysis (Table)4, 6,39,56,57,61-66. Enrolled studies were carried out in six countries (5 in China, 2 in the USA, 1 in the UK, 1 in Canada, 1 in Egypt, and 1 in France), and the publication period ranged from 2013 to 2024. In terms of data extraction, HRs with 95% CIs were obtained directly from survival curves, univariate and multivariate analyses.
| Study | Year | Region | Data extraction | Test method | Outcome measures |
|---|---|---|---|---|---|
| Li et al4 | 2020 | China | Dataset | SC | OS, RFS |
| Alfarsi et al61 | 2018 | UK | Dataset | SC | OS, RFS, DMFS |
| Moamer et al6 | 2019 | Canada | Dataset | SC | RFS, DMFS |
| Ogden et al62 | 2017 | USA | Tissue | M | OS, DMFS |
| Dai et al63 | 2017 | China | Dataset | SC | RFS |
| Gao et al64 | 2020 | China | Dataset | SC | OS |
| Wang et al65 | 2013 | China | Tissue | U | OS |
| Hemida et al66 | 2024 | Egypt | Tissue | M | OS |
| Jinna et al56 | 2023 | USA | Tissue | SC | OS, DMFS |
| Liu et al39 | 2023 | China | Tissue | U | OS |
| Rodrigues-Ferreira et al57 | 2023 | France | Tissue | SC | OS, RFS |
SC, survival curve; M, multivariate; U, univariate; OS, overall survival; RFS, recurrence-free survival; DMFS, distant metastasis-free survival
Quality assessment/ROB
ROB for studies are shown in supplementary figure 1B. Of the chosen seven criteria, three scored as ‘high risk.’ These were ‘random sequence generation,’ ‘allocation concealment,’ and ‘blinding of participants and personnel’. These quality items are essential to ensuring high standards in clinical studies. Furthermore, five items marked as ‘unclear’ across the studies: ‘random sequence generation’, blinding of outcome assessment’, ‘allocation concealment’, ‘blinding of participants and personnel,’ and ‘incomplete outcome data’. However, none of these issues were considered significant. When excluding ‘selective reporting’ and ‘other bias,’ which were mostly rated as ‘unclear’ or ‘high risk,’ all studies still demonstrated cumulative high quality and were not excluded solely due to quality concerns. Overall, the included human studies were of high quality, with the exception of one study, which was rated as moderate quality due to diagnostic limitations and a small sample size30 (Supplementary Table IV)4,6,36,39,57,61-66.
Analysis of KIFs expression in survival
Association of KIFs expression and OS
This meta-analysis included nine studies that reported HRs for OS based on KIFs expression levels, as detailed in supplementary table V4,39,56,57,61,62,64-66. Fixed-effect model was used to identify the association between KIF-expression and OS in BC patients, revealing no significant heterogeneity (I2=27%, Pheterogeneity=0.21). The findings indicated that patients with elevated KIFs expression had significantly shorter OS than those with lower expression (HR=1.77 with 95% CI showed 1.58-1.98 and P<0.00001; Fig. 2A). The funnel plot results indicated absence of publication bias, as shown in supplementary figure 2A.
- A meta-analysis conducted between low and high expression levels of KIFs, (A) OS forest plot; (B) RFS forest plot; (C) DMFS forest plot. I2, Higgins heterogeneity index; CI, confidence intervals; OS, overall survival; RFS, recurrence free survival; DMFS, distant metastasis free survival; HR, hazard ratio; df, degree of freedom. Source: Image was created using Review Manager 5; RevMan 5 software19.
Association between KIFs expression and RFS
Five studies were included in this analysis, which provided HRs for RFS in relation to KIFs expression levels (Supplementary Table VI)4,6,57,61,63. Fixed-effect model was used to assess the association with expression levels of KIFs and their impact on RFS in BC patients with significant heterogeneity (I2=97%, Pheterogeneity=<0.00001). The ratio for RFS was 1.4 for pooled HR (95% CI=1.31-1.49, P=<0.00001), which showed a significant association between poorer RFS and high KIFs expression, as shown in figure 2B. In the funnel plot, there were dots placed on or outside the slant, which means these studies may have a ROB, which may be because the quantity of literature included in this study was small, as shown in supplementary figure 2B.
Association between KIFs expression and distant metastasis-free survival
Four articles were incorporated in the meta-analysis, which provided HRs for DMFS in relation to KIFs expression levels (Supplementary Table VII)6,56,61,62. A fixed-effect model was employed to assess the interaction between high and low expression levels of KIFs and their impact on DMFS in BC patients with no significant heterogeneity (I2=48%, Pheterogeneity=0.12). A pooled HR of 1.72 (95% CI: 1.49-1.99; P<0.00001) indicated a significant association between high KIF expression and poorer DMFS in BC patients, as illustrated in figure 2C. In the funnel plot, the studies had no publication bias, supplementary figure 2C.
Overall, the study findings indicated that KIFs overexpression was closely linked to decreased OS, as well as poorer RFS and DMFS, indicating their potential as prognostic biomarkers for disease progression, relapse and distant metastasis in BC.
Discussion
BC, due to its complexity and heterogeneity, poses challenges in identifying reliable prognostic biomarkers, which are essential for guiding clinical decisions and improving patient outcomes. KIFs have emerged as promising candidates for such biomarkers in BC. We could not identify any meta-analysis conducted previously to the present one to assess the impact of the KIF family on BC prognosis. Dysregulation of kinesin motor proteins has been linked to BC, as altered expression or mutations in these proteins can disrupt cellular transport processes, leading to abnormal cell division, impaired organelle distribution, and disturbed cellular homeostasis.
In our study, high KIF expression levels were associated with a shorter survival ratio in BC patients. Li et al4 showed the chip seq data from the GEO and METABRIC cohort, including 30,951 BC patients. The prognostic significance of 11 KIFs (KIF10, KIF11, KIF14, KIF15, KIF18A, KIF18B, KIF20A, KIF23, KIF2C, KIF4A, and KIFC1) was significantly linked to poorer outcomes across OS, RFS, and DMFS, highlighting their potential in BC prognosis. KIFC1 is essential for centrosome clustering in cancer cells, a process critical due to the frequent occurrence of centrosome amplification, a known characteristic of many that drives genomic instability67. Elevated KIFC1 expression has been observed in various human cancers, such as ovarian, lung, breast, and hepatocellular carcinomas. Further exploration of KIFC1 may offer novel perspectives for developing molecular therapy and targeted cancer therapies. Similarly, KIF18A may contribute to BC progression through the activation of β-catenin. Both KIF18A overexpression and abnormal β-catenin expression are implicated as proto-oncogenes in BC, and their presence may serve as indicators of poor prognosis and tumour aggressiveness.
Triple negative breast cancer (TNBC) is typically diagnosed at an advanced stage, carries a higher risk of visceral metastasis, leads to poor prognosis, and tends to be resistant to conventional receptor-targeted therapies. Although our analysis did not find a significant association between KIF15 expression and prognosis, particularly in TNBC, previous studies indicated that elevated KIF15 levels were linked with poor clinical outcomes in TNBC68. Additionally, separate research on gastric cancer showed an association of higher KIF15 expression in gastric cancer patients with better survival outcomes69. Overall, elevated KIF15 expression is considered a marker of poor prognosis in BC, particularly in TNBC.
Moamer et al6 used the Kaplan-Meier plotter database to analyse the survival data from BC patients for more than 10 years. Their findings revealed that higher KIF5B mRNA levels were associated with worse outcomes, reflected in reduced DMFS and RFS, and highlighted the importance of KIF5B as a potential therapeutic target. Additionally, Wang et al65 reported that patients with elevated KIF26B expression had significantly shorter OS (P=0.004) and lower disease-free survival (DFS) (P=0.001).
Our results showed a significant association between kinesin family members with poor OS, RFS, and DMFS in BC patients. These findings suggest that high KIF expression levels may serve as valuable prognostic indicators of disease progression and recurrence. It is also important to consider the diverse nature of BC, which encompasses multiple subtypes with distinct molecular characteristics. The impact of KIFs on patient survival may vary depending on the specific BC subtype.
There were a few limitations in this systematic review. This review primarily focused on the expression levels of KIF members in BC. The data regarding the expression levels of certain kinesin family members in relation to BC survival analysis were notably limited. The constraints of this study stem from the unavailability of comprehensive data encompassing all kinesin family members. The investigation was therefore restricted by a narrow range of outcome metrics, including only OS, RFS, and DMFS; hence, it failed to provide a more comprehensive evaluation of outcomes, such as disease-free survival (DFS), progression-free survival (PFS), cause-specific survival (CSS), time-to-progression (TTP), and event-free survival (EFS). Despite the implementation of methodologies aimed at identifying publication bias, there remains a probability that research articulating non-significant outcomes has been insufficiently propagated. This situation might lead to an exaggeration of the reported outcomes. Additional empirical research is warranted to corroborate these conclusions.
Overall, this study highlighted the association between KIFs overexpression and poor outcomes in BC, including OS, RFS, and DMFS. These findings point to the potential of KIFs as prognostic markers for disease progression, relapse, and metastasis. However, further research with a larger sample size and detailed information of patients is needed to confirm KIF role in BC prognostication.
Additionally, investigating the specific BC subtypes and their responses to KIFs dysregulation could provide valuable insights into patient survivability. Overall, the findings of this meta-analysis contribute to our understanding of KIFs in BC prognosis and suggest further exploration in clinical settings.
Financial support & sponsorship
The study received funding support as a fellowship grant (Grant no. 2021-11476/CMB-BMS) from Indian Council of Medical Research, New Delhi awarded to first author (S).
Conflicts of Interest
None.
Use of Artificial Intelligence (AI)-Assisted Technology for manuscript preparation
The authors confirm that there was no use of AI-assisted technology for assisting in the writing of the manuscript and no images were manipulated using AI.
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