Ki-67 labeling index as a predictor of response to neoadjuvant chemotherapy in breast cancer

Jain, Praveen; Doval, Dinesh Chandra; Batra, Ullas; Goyal, Pankaj; Bothra, Sneha; Agarwal, Chaturbhuj; Choudhary, Dutta Kumardeep; Yadav, Abhishek; Koyalla, Venkata Pradeep Babu; Sharma, Mukut; Dash, Prasantha Kumar; Talwar, Vineet

doi:10.1093/jjco/hyz012

Cited by 43 publications

(36 citation statements)

References 39 publications

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“…Ki-67 is a biological marker associated with cell proliferation and is regarded as the traditional marker for predicting the response to NACT in BC. 6 In this study, Ki-67 also showed a good predictive performance. These results strongly support previous findings.…”

Section: Discussionsupporting

confidence: 59%

“…These results strongly support previous findings. 6,44 This study also showed that a combination of pathological markers can improve the power of single markers for predicting the response to NACT in BC. TWIST-1 and Ki-67, which showed the best performance for predicting different responses, were combined into a new predictive marker termed predRCB using a linear regression model.…”

Section: Discussionmentioning

confidence: 65%

“…Among the established clinicopathological markers, only Ki-67, estrogen receptor (ER), and human epidermal growth factor receptor 2 (HER2) have shown clear clinical applicability, 4,5 and of these, only Ki-67 was reported to be an accurate biomarker for predicting PCR to NACT. 6 However, the predictive efficacy of a single biomarker remains controversial. Gene expression analysis may improve our understanding of the biological behavior of BC, and although some genes may be useful indicators for the early identification of NACT responses, 7,8 the high costs associated with their analysis limit their routine clinical application.…”

Section: Introductionmentioning

confidence: 99%

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<p>HIF-1α, TWIST-1 and ITGB-1, associated with Tumor Stiffness, as Novel Predictive Markers for the Pathological Response to Neoadjuvant Chemotherapy in Breast Cancer</p>

Zhang

Gao

et al. 2020

CMAR

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Purpose: To investigate the relationship between hypoxia-inducible factor 1-alpha (HIF-1α), Twist family BHLH transcription factor 1 (TWIST-1), and β1 integrin (ITGB-1) expression and tumor stiffness, and evaluate performance of HIF-1α, TWIST-1, and ITGB-1 alone and in combination with Ki-67 for predicting pathological responses to neoadjuvant chemotherapy (NACT) in breast cancer (BC). Patients and Methods: This was a prospective cohort study of 104 BC patients receiving NACT. Tumor stiffness and oxygen score (OS) were evaluated before NACT by shear-wave elastography and optical imaging; HIF-1α, TWIST-1, ITGB-1, and Ki-67 expression were quantitatively assessed by immunohistochemistry of paraffin-embedded tumor samples obtained by core needle biopsy. Indexes were compared among different residual cancer burden (RCB) groups, and associations of HIF-1α, TWIST-1, ITGB-1, and Ki-67 with tumor stiffness and OS were examined. The value of HIF-1α, TWIST-1, ITGB-1, and Ki-67, and a possible new combined index (predRCB) for predicting NACT responses was assessed by receiver operating characteristic (ROC) curves. Results: HIF-1α, TWIST-1, and ITGB-1 expression were positively correlated with tumor stiffness and negatively with OS. Area under the ROC curves (AUCs) measuring the performance of HIF-1α, TWIST-1, ITGB-1, and Ki-67 for predicting responses to NACT were 0.81, 0.85, 0.79, and 0.80 for favorable responses, and 0.83, 0.86, 0.84, and 0.85 for resistant responses, respectively. PredRCB showed better prediction than the other individual indexes for favorable responses (AUC = 0.88) and resistant responses (AUC = 0.92). Conclusion: HIF-1α, TWIST-1, ITGB-1, and Ki-67 performed well in predicting favorable responses and resistance to NACT, and predRCB improved the predictive power of the individual indexes. These results support individualized treatment of BC patients receiving NACT.

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Section: Discussionsupporting

confidence: 59%

Section: Discussionmentioning

confidence: 65%

Section: Introductionmentioning

confidence: 99%

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<p>HIF-1α, TWIST-1 and ITGB-1, associated with Tumor Stiffness, as Novel Predictive Markers for the Pathological Response to Neoadjuvant Chemotherapy in Breast Cancer</p>

Zhang

Gao

et al. 2020

CMAR

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“…Many studies have found that Ki-67 can be used as an important predictor of pCR obtained by chemotherapy. [26] , when Ki≤35% (vs Ki-67> 35%), NAC obtains more pCR (p = 0.0001) [27] , and this is inconsistent with the conclusions of our study. Our study found that patients with Ki-67 <20% did not get better pCR in NAC (p = 1.4 > 0.05).…”

Section: Discussioncontrasting

confidence: 99%

“…Chou et al confirmed that the younger patients (<50years) is the only independent factor favorable for LRR-freesurvival in patients with breast cancer after NAC with concurrent epirubicin and docetaxel [18] . However, other studies have concluded that age is not related to the prognosis of neoadjuvant chemotherapy [27] . In our study, it was found that the patient's age was not significantly related to OS/DFS.…”

Section: Discussionmentioning

confidence: 94%

The relationship between hormone receptor status, tumor size and clinical stage and the efficacy of neoadjuvant chemotherapy for locally advanced breast cancer, predictors of survival, and the establishment of Cox-Based risk prediction model and nomogram

Fengjiao

et al. 2020

Preprint

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Background: Neoadjuvant chemotherapy is currently mainly used for locally advanced breast cancer. However, there is currently no effective way to predict the prognosis of neoadjuvant chemotherapy patients. Methods: All relevant data before and after chemotherapy were collected and evaluate the efficacy of chemotherapy through RECIST1.1 and pathology. Survival curves were generated by the Kaplan-Meier method and compared using the log-rank test. A nomogram was developed using a binary logisti regression model with a cross validation. Results: A total of 158 patients were included in our study. The ORR was 64.6% (cCR, 3.8%; cPR, 60.8%). The pCR rates wer 12.0% for breast tumor and axillary nodes. The pCR rates were 17.1% for breast tumor and 30.4% for axillary nodes. Our study found that only differences in HER-2 status could predict different clinical efficacy, and clinical remission (CR+PR) was more likely to be achieved if HER-2 positive than negative (16.7% vs 7.5%, p=0.05). There was no significant difference in the clinical efficacy of neoadjuvant chemotherapy in age, clinical stage, and molecular classification of patients. In a single factor COX proportional hazard model study, it was found that ER positive relative to HR negative(HR 0.479,CI 95% 0.272-0.844, p=0.011), PR positive relative to PR negative (HR 0.423,CI 95% 0.235-0.763, p=0.004), HER-2 positive relative to HER-2 negative (HR 2.011, CI 95% 1.000-4.042, p=0.050), TNBC (HR 2.229, CI 95% 1.189-4.178, p=0.012), and HER-2 (HR 2.808, CI 95% 1.301-6.062, p=0.009) type are more effective than patients with Luminal type breast cancer 0btain a longer survival time, which is considered a protective factor. A nomogram was developed based on the clinical and statistically significant predictors. ROC curve for 3-year survial with area under the curve = 0.731 (95% confidence interval, 0.663-0.828); ROC curve for 5-year survial with area under the curve = 0.743 (95% confidence interval, 0.652-0.834); ROC curve for 10-year survial with area under the curve = 0.726 (95% confidence interval, 0.639-0.812). Conclusion: In conclusion, the hormone receptor status before chemotherapy can predict the prognosis of patients in advance, and we successfully constructed nomogram, which can help us predict the OS of patients with NAC.

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Prognostic analysis of three forms of Ki‐67 in patients with breast cancer with non‐pathological complete response before and after neoadjuvant systemic treatment

Zhang

Wang

et al. 2023

Cancer Medicine

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Background Patients who do not achieve a pathological complete response (pCR) after neoadjuvant systemic treatment (NST) have a significantly worse prognosis. A reliable predictor of prognosis is required to further subdivide non‐pCR patients. To date, the prognostic role in terms of disease‐free survival (DFS) between the terminal index of Ki‐67 after surgery (Ki‐67 T ) and the combination of the baseline Ki‐67 at biopsy before NST (Ki‐67 B ) and the percentage change in Ki‐67 before and after NST (Ki‐67 C ) has not been compared. Aim This study aimed to explore the most useful form or combination of Ki‐67 that can provide prognostic information to non‐pCR patients. Patients and Methods We retrospectively reviewed 499 patients who were diagnosed with inoperable breast cancer between August 2013 and December 2020 and received NST with anthracycline plus taxane. Results Among all the patients, 335 did not achieve pCR (with a follow‐up period of ≥1 year). The median follow‐up duration was 36 months. The optimal cutoff value of Ki‐67 C to predict a DFS was 30%. A significantly worse DFS was observed in patients with a low Ki‐67 C ( p < 0.001). In addition, the exploratory subgroup analysis showed relatively good internal consistency. Ki‐67 C and Ki‐67 T were considered as independent risk factors for DFS (both p < 0.001). The forecasting model combining Ki‐67 B and Ki‐67 C showed a significantly higher area under the curve at years 3 and 5 than Ki‐67 T ( p = 0.029 and p = 0.022, respectively). Conclusions Ki‐67 C and Ki‐67 T were good independent predictors of DFS, whereas Ki‐67 B was a slightly inferior predictor. The combination of Ki‐67 B and Ki‐67 C is superior to Ki‐67 T for predicting DFS, especially at longer follow‐ups. Regarding clinical application, this combination could be used as a novel indicator for predicting DFS to more clearly identify high‐risk patients.

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Ki-67 labeling index as a predictor of response to neoadjuvant chemotherapy in breast cancer

Cited by 43 publications

References 39 publications

<p>HIF-1α, TWIST-1 and ITGB-1, associated with Tumor Stiffness, as Novel Predictive Markers for the Pathological Response to Neoadjuvant Chemotherapy in Breast Cancer</p>

<p>HIF-1α, TWIST-1 and ITGB-1, associated with Tumor Stiffness, as Novel Predictive Markers for the Pathological Response to Neoadjuvant Chemotherapy in Breast Cancer</p>

The relationship between hormone receptor status, tumor size and clinical stage and the efficacy of neoadjuvant chemotherapy for locally advanced breast cancer, predictors of survival, and the establishment of Cox-Based risk prediction model and nomogram

Prognostic analysis of three forms of Ki‐67 in patients with breast cancer with non‐pathological complete response before and after neoadjuvant systemic treatment

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