Distinguishing Low-Risk Luminal A Breast Cancer Subtypes with Ki-67 and p53 Is More Predictive of Long-Term Survival

Association between CD10 expression and phyllodes tumor: A retrospective case control study

The present study aimed to explore the association between immunohistochemical markers and phyllodes tumor (PT). The retrospective case control study included biopsies from patients with PT who underwent surgical treatment, and patients with fibronenoma (FA), diagnosed in our hospital from October 2014 to May 2021. Differences in microscopic histopathological characteristics and expressions of common immunohistochemical markers (CD10, cluster of differentiation 117 marker, cluster of differentiation 34 marker, tumor protein P53, cell proliferation antigen) for different grades of PT and FA were analyzed. A total of 69 patients were enrolled, of them 34 with PT (12 with benign PT, 13 with borderline PT, and 9 with malignant PT) and 35 with FA. With the increase of tumor malignancy, significant enlargement trend was noted; for FA, most tumor boundaries were well-defined, the stromal distribution was homogeneous, the stromal cellularity was small. In contrast for PT, as the degree of malignancy increased, tumor boundary gradually became ill-defined and the stromal distribution was heterogeneous; stromal cellularity and stromal overgrowth had increased significantly (All P < .05). Multivariate analysis showed that among other markers only CD10 expression (OR = 0.67, 95%CI: -0.88, 2.22, P < .05) was independently associated with PT. The study showed that in addition to histological features, CD10 expression was independently associated with PT and has a potential to be used as a differentiation marker.

Positive p53 Expression Is Associated with Primary Endocrine Therapy Resistance in Locally Advanced Stage Luminal B HER2-Negative Breast Cancer Patients: A Cross-Sectional Study in Indonesia

Luminal B HER2-negative breast cancer (BC) is the most common type in Indonesian BC patients, and frequently manifests with locally advanced staging. Recurrence often occurs within two years of the endocrine therapy course (primary endocrine therapy (ET) resistance). p53 mutation often exists in luminal B HER2-negative BC, but its application as an ET resistance predictor in those populations is still limited. The primary purpose of this research is to evaluate p53 expression and its association with primary ET resistance in luminal B HER2-negative BC. This cross-sectional study compiled 67 luminal B HER2-negative patients' clinical data during their pre-treatment period until they completed a two-year course of endocrine therapy. They were divided into two groups: 29 patients with primary ET resistance and 38 without primary ET resistance. Pre-treatment paraffin blocks from each patient were retrieved, and the p53 expression difference between the two groups was analyzed. Positive p53 expression was significantly higher in patients with primary ET resistance [odds ratio (OR) of 11.78 (95% CI: 3.72-37.37, p-value < 0.0001)]. We conclude that p53 expression could be a beneficial marker for primary ET resistance in locally advanced luminal B HER2-negative BC.

Nomograms for Predicting Disease-Free Survival Based on Core Needle Biopsy and Surgical Specimens in Female Breast Cancer Patients with Non-Pathological Complete Response to Neoadjuvant Chemotherapy

PURPOSE

While a pathologic complete response (pCR) is regarded as a surrogate endpoint for pos-itive outcomes in breast cancer (BC) patients receiving neoadjuvant chemotherapy (NAC), fore-casting the prognosis of non-pCR patients is still an open issue. This study aimed to create and evaluate nomogram models for estimating the likelihood of disease-free survival (DFS) for non-pCR patients.

METHODS

A retrospective analysis of 607 non-pCR BC patients was conducted (2012-2018). After converting continuous variables to categorical variables, variables entering the model were progressively identified by univariate and multivariate Cox regression analyses, and then pre-NAC and post-NAC nomogram models were developed. Regarding their discrimination, ac-curacy, and clinical value, the performance of the models was evaluated by internal and external validation. Two risk assessments were performed for each patient based on two models; patients were separated into different risk groups based on the calculated cut-off values for each model, including low-risk (assessed by the pre-NAC model) to low-risk (assessed by the post-NAC model), high-risk to low-risk, low-risk to high-risk, and high-risk to high-risk groups. The DFS of different groups was assessed using the Kaplan-Meier method.

RESULTS

Both pre-NAC and post-NAC nomogram models were built with clinical nodal (cN) status and estrogen receptor (ER), Ki67, and p53 status (all p < 0.05), showing good discrimination and calibration in both internal and external validation. We also assessed the performance of the two models in four subtypes, with the tri-ple-negative subtype showing the best prediction. Patients in the high-risk to high-risk subgroup have significantly poorer survival rates (p < 0.0001).

CONCLUSION

Two robust and effective nomo-grams were developed to personalize the prediction of DFS in non-pCR BC patients treated with NAC.

Development and Assessment of a Novel Core Biopsy-Based Prediction Model for Pathological Complete Response to Neoadjuvant Chemotherapy in Women with Breast Cancer

Purpose: Pathological complete response (pCR), the goal of NAC, is considered a surrogate for favorable outcomes in breast cancer (BC) patients administrated neoadjuvant chemotherapy (NAC). This study aimed to develop and assess a novel nomogram model for predicting the probability of pCR based on the core biopsy. Methods: This was a retrospective study involving 920 BC patients administered NAC between January 2012 and December 2018. The patients were divided into a primary cohort (769 patients from January 2012 to December 2017) and a validation cohort (151 patients from January 2017 to December 2018). After converting continuous variables to categorical variables, variables entering the model were sequentially identified via univariate analysis, a multicollinearity test, and binary logistic regression analysis, and then, a nomogram model was developed. The performance of the model was assessed concerning its discrimination, accuracy, and clinical utility. Results: The optimal predictive threshold for estrogen receptor (ER), Ki67, and p53 were 22.5%, 32.5%, and 37.5%, respectively (all p < 0.001). Five variables were selected to develop the model: clinical T staging (cT), clinical nodal (cN) status, ER status, Ki67 status, and p53 status (all p ≤ 0.001). The nomogram showed good discrimination with the area under the curve (AUC) of 0.804 and 0.774 for the primary and validation cohorts, respectively, and good calibration. Decision curve analysis (DCA) showed that the model had practical clinical value. Conclusions: This study constructed a novel nomogram model based on cT, cN, ER status, Ki67 status, and p53 status, which could be applied to personalize the prediction of pCR in BC patients treated with NAC.

Markers associated with genomic instability, immunogenicity and immune therapy responsiveness in Metaplastic carcinoma of the breast: Expression of γH2AX, pRPA2, P53, PD-L1 and tumor infiltrating lymphocytes in 76 cases

BACKGROUND

Metaplastic breast cancer (MpBC) is an aggressive subtype of breast carcinoma that is often resistant to conventional chemotherapy. Therefore, novel treatment strategies are urgently needed. Immune check point inhibitors have shown activity in programmed death-ligand 1 (PD-L1) - positive metastatic triple negative breast carcinoma (TNBC), which raises the possibility that immunotherapy may also be effective in MpBC as most of the MpBCs are triple negative. The aim of the present study was to assess genomic instability and immunogenicity in tumor specimens of patients with MpBC.

METHODS

A total of 76 patients diagnosed with MpBC over a 15-year period were included in the study. We performed immunohistochemical analyses for tumor cell PD-L1, immune cell PD-L1 and p53 on tissue microarrays (TMAs), analyzed stromal and intratumoral tumor infiltrating lymphocytes (TILs) from hematoxylin and eosin-stained (H&E) slides and scored gamma-H2AX (γH2AX) and phosphorylated-RPA2 (pRPA2) from whole tissue sections. We correlated marker expression with clinicopathologic features and clinical outcome.

RESULTS

All tumors expressed γH2AX and pRPA2 with median expressions of 43% and 44%. P53- (68%), tumor cell PD-L1- (59%) and immune cell PD-L1-positivity (62%) were common in MpBCs. Median stromal TIL and intratumoral TIL counts were 5% and 0. The spindle and squamous cell carcinomas expressed the highest levels of PD-L1 and TILs, and carcinoma with mesenchymal differentiation the lowest.

CONCLUSIONS

MpBC appears to be an immunogenic cancer with high genomic instability and frequent PD-L1-positivity, implying that check point inhibitors might be effective in MpBC. Expression levels of PD-L1 and TILs varied across different histologic subtypes, suggesting that immunotherapy might be less effective in carcinoma with mesenchymal differentiation.

p53 Mutation as Plausible Predictor for Endocrine Resistance Therapy in Luminal Breast Cancer

Endocrine therapy resistance in Luminal Breast Cancer is a significant issue to be tackled, but currently, no specific biomarker could be used to anticipate this event. p53 mutation is widely known as one of Breast Cancer's most prominent genetic alterations. Its mutation could generate various effects in Estrogen Receptor and Progesterone Receptor molecular works, tangled in events leading to the aggravation of endocrine therapy resistance. Hence the possibility of p53 mutation utilization as an endocrine therapy resistance predictive biomarker is plausible. The purpose of this review is to explore the latest knowledge of p53 role in Estrogen Receptor and Progesterone Receptor molecular actions, thus aggravating the Endocrine Therapy resistance in Luminal Breast Cancer, from which we could define possibilities and limitations to utilize p53 as the predictive biomarker of endocrine therapy resistance in Luminal Breast Cancer.

Prognostic significance of RNA-based TP53 pathway function among estrogen receptor positive and negative breast cancer cases

TP53 and estrogen receptor (ER) are essential in breast cancer development and progression, but TP53 status (by DNA sequencing or protein expression) has been inconsistently associated with survival. We evaluated whether RNA-based TP53 classifiers are related to survival. Participants included 3213 women in the Carolina Breast Cancer Study (CBCS) with invasive breast cancer (stages I-III). Tumors were classified for TP53 status (mutant-like/wildtype-like) using an RNA signature. We used Cox proportional hazards models to estimate covariate-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for breast cancer-specific survival (BCSS) among ER- and TP53-defined subtypes. RNA-based results were compared to DNA- and IHC-based TP53 classification, as well as Basal-like versus non-Basal-like subtype. Findings from the diverse (50% Black), population-based CBCS were compared to those from the largely white METABRIC study. RNA-based TP53 mutant-like was associated with BCSS among both ER-negatives and ER-positives (HR (95% CI) = 5.38 (1.84-15.78) and 4.66 (1.79-12.15), respectively). Associations were attenuated when using DNA- or IHC-based TP53 classification. In METABRIC, few ER-negative tumors were TP53-wildtype-like, but TP53 status was a strong predictor of BCSS among ER-positives. In both populations, the effect of TP53 mutant-like status was similar to that for Basal-like subtype. RNA-based measures of TP53 status are strongly associated with BCSS and may have value among ER-negative cancers where few prognostic markers have been robustly validated. Given the role of TP53 in chemotherapeutic response, RNA-based TP53 as a prognostic biomarker could address an unmet need in breast cancer.

Primary Breast Tumors with Mesenchymal Morphology

Overview Mesenchymal tumors of the breast are rare. Few epithelial tumors also have mesenchymal components. It is crucial to identify these as per histogenesis. This can be facilitated by markers of epithelial–mesenchymal transition (EMT).

Objectives The aim of this study was to categorize the breast lesions with mesenchymal morphology and to study EMT on immunohistochemistry (IHC).

Materials and Methods This is a retrospective study of 5-year duration from January 2015 to December 2019. Inclusion criteria: all breast lesions showing mesenchymal/nonepithelial morphology, complete or partial, on histology. Exclusion criteria: Mammary carcinomas without any mesenchymal/nonepithelial morphology, fibroadenomas, and lymphomas. Demographics, clinical, gross examination, histology, and IHC findings of selected cases were reviewed and recorded. Three additional markers p53, E-cadherin, and β-catenin were performed.

Statistical Analysis Used Frequency calculation for each variable (IHC).

Results Thirteen (2.5%) out of total 510 breast specimens showed mesenchymal histology. Of these, five (38.5%) were metaplastic breast carcinomas (MBC), four (31%) were phyllodes tumor (PT), and one (7.7%) case each of malignant peripheral nerve sheath tumor, primary stromal sarcoma of breast, pseudoangiomatous stromal hyperplasia, and myofibroblastoma. Loss of E-cadherin was seen in 4/5 (80%) MBCs and was retained in ductal component of PTs. p53 was not expressed in any of the tumors except 3/5 (60%) MBCs. β-Catenin was aberrant in all MBCs.

Conclusions Primary breast tumors with mesenchymal morphology present a spectrum ranging from benign mesenchymal, fibroepithelial neoplasms to malignant tumors of mesenchymal and epithelial origin. Loss of E-cadherin, expression of p53, and aberrant expression of β-catenin are suggestive of EMT and molecular heterogeneity of MBCs.

Assessment of programmed death-ligand 1 receptor immunohistochemical expression and its association with tumor-infiltrating lymphocytes and p53 status in triple-negative breast cancer

Breast cancer (BC) is the second most frequent type of cancer for both sexes combined, after lung cancer. Triple-negative BC (TNBC) molecular subtype is characterized by lack of estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2) immunoexpression or amplification and represent 10-20% of all BC cases. The issue of the present study was to analyze the associations between programmed death-ligand 1 (PD-L1) immunoexpression and distribution of stromal tumor-infiltrating lymphocytes (stTILs) combined with clinico-morphological features of patients with TNBC. Secondly, our research evaluated PD-L1 immunoexpression as a prognostic factor and its correlation with p53 immunoexpression. Thirty cases with primary TNBC without prior neoadjuvant therapy were included in this research. stTILs were identified in all cases, most of them with low distribution (66.7%). A positive immunoreaction for PD-L1 was observed in 40% of cases. The PD-L1 immunoexpression was statistically significant associated with age, pathological tumor size, lymphovascular invasion, stTILs level, the presence of cluster of differentiation 8-positive (CD8+) TILs and p53 immunoexpression. In the present study, a positive PD-L1 immunoexpression was associated with a worse distant metastasis free survival (DMFS). We also found not only that high stTILs level were associated with a better DMFS but also that there was a statistically significant association between stTILs level and PD-L1 immunoexpression. Our results bring new insights to the fine connections between tumor microenvironment and molecular changes of TNBC. It helps us to better understand these aggressive tumors to identify the more useful biomarkers for predicting the response to adjuvant therapy and can represent a method for selecting the most suitable patients for immunotherapy.

Prediction of Oncotype DX recurrence score using deep multi-layer perceptrons in estrogen receptor-positive, HER2-negative breast cancer

Oncotype DX (ODX) is a multi-gene expression signature designed for estrogen receptor (ER)-positive and human epidermal growth factor receptor 2 (HER2)-negative breast cancer patients to predict the recurrence score (RS) and chemotherapy (CT) benefit. The aim of our study is to develop a prediction tool for the three RS's categories based on deep multi-layer perceptrons (DMLP) and using only the morphoimmunohistological variables. We performed a retrospective cohort of 320 patients who underwent ODX testing from three French hospitals. Clinico-pathological characteristics were recorded. We built a supervised machine learning classification model using Matlab software with 152 cases for the training and 168 cases for the testing. Three classifiers were used to learn the three risk categories of the ODX, namely the low, intermediate, and high risk. Experimental results provide the area under the curve (AUC), respectively, for the three risk categories: 0.63 [95% confidence interval: (0.5446, 0.7154), p < 0.001], 0.59 [95% confidence interval: (0.5031, 0.6769), p < 0.001], 0.75 [95% confidence interval: (0.6184, 0.8816), p < 0.001]. Concordance rate between actual RS and predicted RS ranged from 53 to 56% for each class between DMLP and ODX. The concordance rate of low and intermediate combined risk group was 85%.We developed a predictive machine learning model that could help to define patient's RS. Moreover, we integrated histopathological data and DMLP results to select tumor for ODX testing. Thus, this process allows more relevant use of histopathological data, and optimizes and enhances this information.

HMNPPID-human malignant neoplasm protein-protein interaction database

BACKGROUND

Protein-protein interaction (PPI) information extraction from biomedical literature helps unveil the molecular mechanisms of biological processes. Especially, the PPIs associated with human malignant neoplasms can unveil the biology behind these neoplasms. However, such PPI database is not currently available.

RESULTS

In this work, a database of protein-protein interactions associated with 171 kinds of human malignant neoplasms named HMNPPID is constructed. In addition, a visualization program, named VisualPPI, is provided to facilitate the analysis of the PPI network for a specific neoplasm.

CONCLUSIONS

HMNPPID can hopefully become an important resource for the research on PPIs of human malignant neoplasms since it provides readily available data for healthcare professionals. Thus, they do not need to dig into a large amount of biomedical literatures any more, which may accelerate the researches on the PPIs of malignant neoplasms.

Clinicopathological and epidemiological significance of breast cancer subtype reclassification based on p53 immunohistochemical expression

TP53 mutations are common in breast cancer and are typically associated with more aggressive tumor characteristics, but little is known about the clinicopathological and epidemiological relevance of p53 protein expression, a TP53 mutation surrogate, in breast cancer subtypes. In this study of 7226 Chinese women with invasive breast cancer, we defined breast cancer subtypes using immunohistochemical (IHC) measures of hormone receptors and HER2 in conjunction with histologic grade. p53 expression status was then used to further stratify subtypes into p53-positive and p53-negative. Odds ratios (ORs) and 95% confidence intervals (CIs) in case-only logistic regression analyses were used to examine heterogeneity across different subtypes. The frequency of p53 protein expression varied by breast cancer subtype, being lowest in the luminal A-like and highest in the triple-negative and HER2-enriched subtypes (P-value < 0.01). In luminal A-like and B-like/HER2-negative subtypes, p53 positivity was associated with early-onset tumors, high grade, high proliferative index, and basal marker (CK5/6 and EGFR) expression. Further, compared with luminal A-like/p53-negative patients, A-like/p53-positive patients were more likely to be parous [adjusted OR parous vs. nulliparous = 2.67 (1.60, 4.51); P-value < 0.01] and to have breastfed [adjusted OR ever vs. never = 1.38 (1.03, 1.85); P-value = 0.03]. p53 positivity was not associated with examined clinical and risk factors in other tumor subtypes. Overall, these findings suggest that p53 expression, which is readily available in many settings, can be used to identify phenotypes of luminal A-like breast cancer with distinct clinical and epidemiological implications.

Differential expression of senescence tumour markers and its implications on survival outcomes of breast cancer patients

Breast cancer is a heterogeneous disease displaying different histopathological characteristics, molecular profiling and clinical behavior. This study describes the expression patterns of senescence markers P53, DEC1 and DCR2 and assesses their significance on patient survival as a single or combined marker with P16 or P14 using breast cancer progression series. One thousand and eighty (1080) patients with primary invasive ductal carcinoma, no special type, were recruited through an 11-year retrospective study period. We constructed tissue microarrays of normal, benign hyperplasia, ductal carcinoma in situ and invasive ductal carcinoma from each patient and performed immunohistochemical staining to study the protein expression. Statistical analysis includes Pearson chi-square, Kaplan-Meier log ran test and Cox proportional hazard regression were undertaken to determine the associations and predict the survival outcomes. P53, DEC1 and DCR2 expression correlated significantly with normal, benign, premalignant and malignant tissues with (p<0.05). The expression profile of these genes increases from normal to benign to premalignant and plateaued from premalignant to malignant phenotype. There is a significant association between P53 protein expression and age, grade, staging, lymphovascular invasion, estrogen receptor, progesterone receptor and HER2 whereas DCR2 protein expression significantly correlated with tumour grade, hormone receptors status and HER2 (p<0.05 respectively). P53 overexpression correlated with increased risk of relapse (p = 0.002) specifically in patients who did not receive hormone therapy (p = 0.005) or chemotherapy (p<0.0001). The combination of P53+/P16+ is significantly correlated with poor overall and disease-free survival, whereas a combination of P53+/P14+ is associated with worse outcome in disease-free survival (p<0.05 respectively). P53 overexpression appears to be a univariate predictor of poor disease-free survival. The expression profiles of DEC1 and DCR2 do not appear to correlate with patient survival outcomes. The combination of P53 with P16, rather P53 expression alone, appears to provide more useful clinical information on patient survival outcomes in breast cancer.

Prognostic value of immunohistochemically detected p53 in adjuvant chemotherapy-treated triple negative breast cancer

Mutations of the p53 gene are the most common genomic alterations associated with triple-negative breast cancer (TNBC) and are reported in 60-88% cases. Despite the high incidence of such mutations, there is no consensus about the clinical application of p53 detection in breast cancer management. This study investigates the prognostic value of immunohistochemically detected p53 in TNBC patients who received adjuvant chemotherapy. We reviewed the clinicopathologic features of 1088 TNBC patients who received curative surgery and adjuvant chemotherapy. Immunohistochemically, nuclear staining of >10% was defined as p53 "positive." Of the total 1088 TNBC patients, 709 (65.2%) had no lymph node metastasis (N0). Among the N0 patients, 408 (57.5%) were p53- positive (p53+), and 301 (42.5%) were p53- negative (p53-). p53 + tumors showed a tendency for better breast cancer-specific survival (BCSS, p = 0.052) and overall survival (OS, p = 0.079) compared to p53- tumors. In multivariate analysis, p53 + tumors showed significantly better BCSS (p53 + vs. p53-; HR 2.8, 95% confidence interval: 1.1-7.3, p = 0.034); however, in TNBC patients with lymph node metastasis, there was no correlation between p53 status, clinicopathologic characteristics, and survival. Consequently, in TNBC patients who received adjuvant chemotherapy, immunohistochemical p53 expression was associated with better BCSS in N0 patients.

The Notch Pathway in Breast Cancer Progression

Objective

Notch signaling pathway is a vital parameter of the mammalian vascular system. In this review, the authors summarize the current knowledge about the impact of the Notch signaling pathway in breast cancer progression and the therapeutic role of Notch's inhibition.

Methods

The available literature in MEDLINE, PubMed, and Scopus, regarding the role of the Notch pathway in breast cancer progression was searched for related articles from about 1973 to 2017 including terms such as “Notch,” “Breast Cancer,” and “Angiogenesis.” Results. Notch signaling controls the differentiation of breast epithelial cells during normal development. Studies confirm that the Notch pathway has a major participation in breast cancer progression through overexpression and/or abnormal genetic type expression of the notch receptors and ligands that determine angiogenesis. The cross-talk of Notch and estrogens, the effect of Notch in breast cancer stem cells formation, and the dependable Notch overexpression during breast tumorigenesis have been studied enough and undoubtedly linked to breast cancer development. The already applied therapeutic inhibition of Notch for breast cancer can drastically change the course of the disease.

Conclusion

Current data prove that Notch pathway has a major participation and multiple roles during breast tumor progression. Inhibition of Notch receptors and ligands provides innovative therapeutic results and could become the therapy of choice in the next few years, even though further research is needed to reach safe conclusions.

P53 and Ki-67 as prognostic markers in triple-negative breast cancer patients

Triple-negative breast cancer (TNBC) is an aggressive subgroup of breast cancer lack of effective target therapy. This study was to investigate the prognostic role of p53 and Ki-67 in 156 cases of TNBC patients. Logistic regression analysis was used to examine the association between clinical parameters and recurrence. Univariate and multivariate analyses were used to examine the association between clinical characteristics and disease-free survival (DFS) or overall survival (OS). Survival analyses using the Kaplan-Meier method were performed to examine the association between p53/Ki-67 and DFS and OS. Our data showed that p53 was positive in 71.3% and the Ki-67 high index was in 82.8% of TNBC. Elevated p53 and Ki-67 were associated with histological grade. The tumor size, lymph node involvement, and p53 expression are associated with risk of recurrence. Tumor size, lymph node involvement, family history, Ki-67 and p53 are independent variables associated with either DFS or OS. TNBC patients with positive p53 or Ki-67 high index or family history of cancer have a significant association with worse prognosis. This study suggests that p53, Ki-67 and family history are useful prognostic markers in TNBC.

HER2 expression is a strong independent predictor of nodal metastasis in breast cancer

Identification of metastatic potential of breast cancer cells is necessary for proper management of this disease. This work aimed to estimate likelihood of axillary lymph node (ALN) involvement in breast cancer patients based on human epidermal growth factor receptor 2 (HER2) expression. Primary tumors of 317 breast cancer patients were evaluated for estrogen receptor (ER), progesterone receptor (PR) and HER2 expression by immunohistochemistry. The validity of these molecules to predict ALN metastasis was measured statistically and compared to predictive effect of other clinicopathological parameters. ER, PR and HER2 expression was detected in 75.7%, 73.2% and 19.9% of tumors, respectively. Although increased tumor size and grade, ER and PR negativity and HER2 positivity were strong indicators of ALN metastasis on univariate analyses, only tumor size and HER2 expression were independent predictors of ALN involvement on multivariate analysis. ROC curve showed a strong validity of the model using these two parameters to predict ALN status (AUC 0.86; p<0001). HER2-rich, luminal B and triple negative tumors had 6.87, 6.32 and 3.58 times increased risk of metastasis compared to luminal A tumors; respectively. HER2 expression in pT1 and pT2 tumors raised the risk of ALN metastasis by 7.7 and 7.6 times, respectively and grade 1 and 2 tumors that expressed HER2 were 16.0 and 7.8 times more likely to have ALN metastasis, respectively. To conclude, HER2 expression is associated with a significant rise of metastatic potential of breast cancer cells and could be a strong indicator of regional and distant metastasis of breast cancer.

USP7 promotes cell proliferation through the stabilization of Ki-67 protein in non-small cell lung cancer cells

The Ki-67 antigen (Ki-67) is the most reliable immunohistochemical marker for evaluation of cell proliferation in non-small cell lung cancer. However, the mechanisms underlying the regulation of protein levels of Ki-67 in non-small cell lung cancer have remained elusive. In this study, we found that Ki-67 and ubiquitin-specific processing protease 7 (USP7) protein were highly expressed in the nucleus of non-small cell lung cancer cells. Furthermore, statistical analysis uncovered the existence of a strong correlation between Ki-67 and USP7 levels. We could also show that the protein levels of Ki-67 in non-small cell lung cancer cells significantly decreased after treatment with P22077, a selective chemical inhibitor of USP7, while the Ki-67 mRNA levels were unperturbed. Similar results were obtained by knocking down USP7 using short hairpin RNA (shRNA) in lung cancer cells. Interestingly, we noticed that ubiquitination levels of Ki-67 increased dramatically in USP7-silenced cells. The tests in vitro and vivo showed a significant delay in tumor cell growth upon knockdown of USP7. Additionally, drug sensitivity tests indicated that USP7-silenced A549 cells had enhanced sensitivity to paclitaxel and docetaxel, while there was no significant change in sensitivity toward carboplatin and cisplatin. Taken together, these data strongly suggest that the overexpression of USP7 might promote cell proliferation by deubiquitinating Ki-67 protein, thereby maintaining its high levels in the non-small cell lung cancer. Our study also hints potential for the development of deubiquitinase-based therapies, especially those targeting USP7 to improve the condition of patients diagnosed with non-small cell lung cancer.

A Bayesian algorithm for detecting differentially expressed proteins and its application in breast cancer research

Presence of considerable noise and missing data points make analysis of mass-spectrometry (MS) based proteomic data a challenging task. The missing values in MS data are caused by the inability of MS machines to reliably detect proteins whose abundances fall below the detection limit. We developed a Bayesian algorithm that exploits this knowledge and uses missing data points as a complementary source of information to the observed protein intensities in order to find differentially expressed proteins by analysing MS based proteomic data. We compared its accuracy with many other methods using several simulated datasets. It consistently outperformed other methods. We then used it to analyse proteomic screens of a breast cancer (BC) patient cohort. It revealed large differences between the proteomic landscapes of triple negative and Luminal A, which are the most and least aggressive types of BC. Unexpectedly, majority of these differences could be attributed to the direct transcriptional activity of only seven transcription factors some of which are known to be inactive in triple negative BC. We also identified two new proteins which significantly correlated with the survival of BC patients, and therefore may have potential diagnostic/prognostic values.