利用人工智能预测癌症的易感性、复发性和生存期

癌症具有较高的发病率和致死率,对人类健康具有重大威胁。癌症预后分析可以有效避免过度治疗及医疗资源的浪费,为医务人员及家属进行医疗决策提供科学依据,已成为癌症研究的必要条件。随着近年来人工智能技术的迅速发展,对癌症患者的预后情况进行自动化分析成为可能。此外,随着医疗信息化的发展,智慧医疗的理念受到广泛关注。癌症患者作为智慧医疗的重要组成部分,对其进行有效的智能预后分析十分必要。本文综述现有基于机器学习的癌症预后方法。首先,对机器学习与癌症预后进行概述,介绍癌症预后及相关的机器学习方法,分析机器学习在癌症预后中的应用;然后,对基于机器学习的癌症预后方法进行归纳,包括癌症易感性预测、癌症复发性预测、癌症生存期预测,梳理了它们的研究现状、涉及到的癌症类型与数据集、用到的机器学习方法及预后性能、特点、优势与不足;最后,对癌症预后方法进行总结与展望。     

Androgen Receptor (AR), E-Cadherin,and Ki-67 as Emerging Targets and Novel Prognostic Markers in Triple-Negative Breast Cancer (TNBC) Patients

BackgroundTNBC is an aggressive subset of breast cancer (BC) without specific target therapy.MethodsThis observational, retrospective study included 45 cases of TNBC. The aim of this study was to evaluate the expression of the AR, E-cadherin and Ki-67 in relation to histological type, time to relapse and overall survival (OS). Immunohistochemistry (IHC) was carried out on formalin-fixed paraffin-embedded tumor samples obtained from patients defined TNBC.ResultsThe AR was positive (IHC >10%) in 26.6%. E-cadherin (CDH1) expression was considered positive if the score was ≥ 2. This expression was negative in 53.3% cases. The Ki-67 index was ≥ 20% in 37.7%. Univariate analyses showed that AR, CDH1 and Ki-67 are significantly associated with OS. Multivariate analysis showed that AR and Ki-67 expression are independent variables associated with OS. The statistical analysis showed that patients with AR negative and Ki-67 positive expression have a significant correlation with poor outcome.ConclusionsOur data suggest that the combination of AR and E-cadherin expression as well as Ki-67 status might be useful prognostic markers in TNBC. Hence, these molecular determinants could play an interesting role to classify subgroups of TNBC.     

乳腺化生性癌的病理特征、复发和生存情况分析

目的:探讨乳腺化生性癌的病理特征、复发和生存情况。方法:选取我院于2002年1月至2015年12月期间收治的7例乳腺化生性癌患者临床病历资料进行回顾性分析,讨论乳腺化生性癌的病理特点和鉴别诊断、组织起源以及治疗预后等。结果:7例乳腺化生性癌PR、ER和HER-2均显示为阴性,广谱CK则显示为阳性;所有入选患者均显示EGFR阳性,其中有3例患者显示p53阳性,4例患者显示CK5/6阳性。此外,3例患者经腋窝淋巴结清扫后显示有2例患者出现腋窝淋巴结转移,4例患者经前哨淋巴结活检后结果:显示无癌转移。结论:乳腺化生性癌在临床上属于乳腺癌中较为罕见的亚型,其生物学行为和生存预后均不佳,HER-2和PR、ER等多显示为阴性,容易复发,目前主要治疗方法:为在手术治疗的基础上加以放射治疗。     

A Prognostic Gene Signature for Metastasis-Free Survival of Triple Negative Breast Cancer Patients

Although triple negative breast cancers (TNBC) are the most aggressive subtype of breast cancer, they currently lack targeted therapies. Because this classification still includes a heterogeneous collection of tumors, new tools to classify TNBCs are urgently required in order to improve our prognostic capability for high risk patients and predict response to therapy. We previously defined a gene expression signature, RKIP Pathway Metastasis Signature (RPMS), based upon a metastasis-suppressive signaling pathway initiated by Raf Kinase Inhibitory Protein (RKIP). We have now generated a new BACH1 Pathway Metastasis gene signature (BPMS) that utilizes targets of the metastasis regulator BACH1. Specifically, we substituted experimentally validated target genes to generate a new BACH1 metagene, developed an approach to optimize patient tumor stratification, and reduced the number of signature genes to 30. The BPMS significantly and selectively stratified metastasis-free survival in basal-like and, in particular, TNBC patients. In addition, the BPMS further stratified patients identified as having a good or poor prognosis by other signatures including the Mammaprint® and Oncotype® clinical tests. The BPMS is thus complementary to existing signatures and is a prognostic tool for high risk ER-HER2- patients. We also demonstrate the potential clinical applicability of the BPMS as a single sample predictor. Together, these results reveal the potential of this pathway-based BPMS gene signature to identify high risk TNBC patients that can respond effectively to targeted therapy, and highlight BPMS genes as novel drug targets for therapeutic development.     

三阴乳腺癌的异质性及靶向治疗

三阴乳腺癌指雌激素受体(ER)、孕激素受体(PR)、人表皮生长因子受体2(HER-2)均为阴性的乳腺癌,占乳腺癌的15%~20%,具有侵袭转移率高、总生存率低、预后差等特点。三阴乳腺癌有很强的异质性,根据其基因表达特征,可分为基底细胞样1型、基底细胞样2型、间质型、间质干细胞型等7个亚类。由于其不表达ER、PR和HER-2,因此内分泌治疗和抗HER-2治疗无效,通常以化疗作为主要治疗方法。近年来,对其靶向治疗如EGFR、PARP、SRC等靶向治疗已有大量研究与应用报道,并显示了一定的治疗效果,提示靶向治疗是未来三阴乳腺癌的治疗方向。我们简要综述三阴乳腺癌的异质性、靶向治疗及预后诊断。     

Prediction of Breast Cancer Survival Using Clinical and Genetic Markers by Tumor Subtypes

Purpose

To identify the genetic variants associated with breast cancer survival, a genome-wide association study (GWAS) was conducted of Korean breast cancer patients.

Methods

From the Seoul Breast Cancer Study (SEBCS), 3,226 patients with breast cancer (1,732 in the discovery and 1,494 in the replication set) were included in a two-stage GWAS on disease-free survival (DFS) by tumor subtypes based on hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2). The associations of the re-classified combined prognostic markers through recursive partitioning analysis (RPA) of DFS for breast cancer were assessed with the Cox proportional hazard model. The prognostic predictive values of the clinical and genetic models were evaluated by Harrell’s C.

Results

In the two-stage GWAS stratified by tumor subtypes, rs166870 and rs10825036 were consistently associated with DFS in the HR+ HER2- and HR- HER2- breast cancer subtypes, respectively (P _rs166870=2.88×10^-7 and P _rs10825036=3.54×10^-7 in the combined set). When patients were classified by the RPA in each subtype, genetic factors contributed significantly to differentiating the high risk group associated with DFS inbreast cancer, specifically the HR+ HER2- (P _discovery=1.18×10^-8 and P _replication=2.08×10^-5) and HR- HRE2- subtypes (P _discovery=2.35×10^-4 and P _replication=2.60×10^-2). The inclusion of the SNPs tended to improve the performance of the prognostic models consisting of age, TNM stage and tumor subtypes based on ER, PR, and HER2 status.

Conclusion

Combined prognostic markers that include clinical and genetic factors by tumor subtypes could improve the prediction of survival in breast cancer.     

Modelling Circulating Tumour Cells for Personalised Survival Prediction in Metastatic Breast Cancer

Ductal carcinoma is one of the most common cancers among women, and the main cause of death is the formation of metastases. The development of metastases is caused by cancer cells that migrate from the primary tumour site (the mammary duct) through the blood vessels and extravasating they initiate metastasis. Here, we propose a multi-compartment model which mimics the dynamics of tumoural cells in the mammary duct, in the circulatory system and in the bone. Through a branching process model, we describe the relation between the survival times and the four markers mainly involved in metastatic breast cancer (EPCAM, CD47, CD44 and MET). In particular, the model takes into account the gene expression profile of circulating tumour cells to predict personalised survival probability. We also include the administration of drugs as bisphosphonates, which reduce the formation of circulating tumour cells and their survival in the blood vessels, in order to analyse the dynamic changes induced by the therapy.We analyse the effects of circulating tumour cells on the progression of the disease providing a quantitative measure of the cell driver mutations needed for invading the bone tissue. Our model allows to design intervention scenarios that alter the patient-specific survival probability by modifying the populations of circulating tumour cells and it could be extended to other cancer metastasis dynamics.     

KIBRA (WWC1) Is a Metastasis Suppressor Gene Affected by Chromosome 5q Loss in Triple-Negative Breast Cancer

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Strategy for SRM-based Verification of Biomarker Candidates Discovered by iTRAQ Method in Limited Breast Cancer Tissue Samples

Since LC-MS-based quantitative proteomics has become increasingly applied to a wide range of biological applications over the past decade, numerous studies have performed relative and/or absolute abundance determinations across large sets of proteins. In this study, we discovered prognostic biomarker candidates from limited breast cancer tissue samples using discovery-through-verification strategy combining iTRAQ method followed by selected reaction monitoring/multiple reaction monitoring analysis (SRM/MRM). We identified and quantified 5122 proteins with high confidence in 18 patient tissue samples (pooled high-risk (n = 9) or low-risk (n = 9)). A total of 2480 proteins (48.4%) of them were annotated as membrane proteins, 16.1% were plasma membrane and 6.6% were extracellular space proteins by Gene Ontology analysis. Forty-nine proteins with >2-fold differences in two groups were chosen for further analysis and verified in 16 individual tissue samples (high-risk (n = 9) or low-risk (n = 7)) using SRM/MRM. Twenty-three proteins were differentially expressed among two groups of which MFAP4 and GP2 were further confirmed by Western blotting in 17 tissue samples (high-risk (n = 9) or low-risk (n = 8)) and Immunohistochemistry (IHC) in 24 tissue samples (high-risk (n = 12) or low-risk (n = 12)). These results indicate that the combination of iTRAQ and SRM/MRM proteomics will be a powerful tool for identification and verification of candidate protein biomarkers.     

Molecular Characteristics and Metastasis Predictor Genes of Triple-Negative Breast Cancer: A Clinical Study of Triple-Negative Breast Carcinomas

Background

Triple-negative breast cancer is a subtype of breast cancer with aggressive tumor behavior and distinct disease etiology. Due to the lack of an effective targeted medicine, treatment options for triple-negative breast cancer are few and recurrence rates are high. Although various multi-gene prognostic markers have been proposed for the prediction of breast cancer outcome, most of them were proven clinically useful only for estrogen receptor-positive breast cancers. Reliable identification of triple-negative patients with a favorable prognosis is not yet possible.

Methodology/Principal Findings

Clinicopathological information and microarray data from 157 invasive breast carcinomas were collected at National Taiwan University Hospital from 1995 to 2008. Gene expression data of 51 triple-negative and 106 luminal breast cancers were generated by oligonucleotide microarrays. Hierarchical clustering analysis revealed that the majority (94%) of triple-negative breast cancers were tightly clustered together carrying strong basal-like characteristics. A 45-gene prognostic signature giving 98% predictive accuracy in distant recurrence of our triple-negative patients was determined using the receiver operating characteristic analysis and leave-one-out cross validation. External validation of the prognostic signature in an independent microarray dataset of 59 early-stage triple-negative patients also obtained statistical significance (hazard ratio 2.29, 95% confidence interval (CI) 1.04–5.06, Cox P = 0.04), outperforming five other published breast cancer prognostic signatures. The 45-gene signature identified in this study revealed that TGF-β signaling of immune/inflammatory regulation may play an important role in distant metastatic invasion of triple-negative breast cancer.

Conclusions/Significance

Gene expression data and recurrence information of triple-negative breast cancer were collected and analyzed in this study. A novel set of 45-gene signature was found to be statistically predictive in disease recurrence of triple-negative breast cancer. The 45-gene signature, if further validated, may be a clinically useful tool in risk assessment of distant recurrence for early-stage triple-negative patients.     

A Probable Risk Factor of Female Breast Cancer: Study on Benign and Malignant Breast Tissue Samples

The study reports enhanced Fe, Cu, and Zn contents in breast tissues, a probable risk factor of breast cancer in females. Forty-one formalin-fixed breast tissues were analyzed using atomic absorption spectrophotometry. Twenty malignant, six adjacent to malignant and 15 benign tissues samples were investigated. The malignant tissues samples were of grade 11 and type invasive ductal carcinoma. The quantitative comparison between the elemental levels measured in the two types of specimen (benign and malignant) tissues (removed after surgery) suggests significant elevation of these metals (Fe, Cu, and Zn) in the malignant tissue. The specimens were collected just after mastectomy of women aged 19 to 59 years from the hospitals of Islamabad and Rawalpindi, Pakistan. Most of the patients belong to urban areas of Pakistan. Findings of study depict that these elements have a promising role in the initiation and development of carcinoma as consistent pattern of elevation for Fe, Cu, and Zn was observed. The results showed the excessive accumulation of Fe (229?±?121 mg/L) in malignant breast tissue samples of patients (p?<?0.05) to that in benign tissues samples (49.1?±?11.4 mg/L). Findings indicated that excess accumulation of iron in malignant tissues can be a risk factor of breast cancer. In order to validate our method of analysis, certified reference material muscle tissue lyophilized (IAEA) MA-M-2/TM was analyzed for metal studied. Determined concentrations were quite in good agreement with certified levels. Asymmetric concentration distribution for Fe, Cu, and Zn was observed in both malignant and benign tissue samples.     

Protein Expression of DNA Damage Repair Proteins Dictates Response to Topoisomerase and PARP Inhibitors in Triple-Negative Breast Cancer

Patients with metastatic triple-negative breast cancer (TNBC) have a poor prognosis. New approaches for the treatment of TNBC are needed to improve patient survival. The concept of synthetic lethality, brought about by inactivating complementary DNA repair pathways, has been proposed as a promising therapeutic option for these tumors. The TNBC tumor type has been associated with BRCA mutations, and inhibitors of Poly (ADP-ribose) polymerase (PARP), a family of proteins that facilitates DNA repair, have been shown to effectively kill BRCA defective tumors by preventing cells from repairing DNA damage, leading to a loss of cell viability and clonogenic survival. Here we present preclinical efficacy results of combining the PARP inhibitor, ABT-888, with CPT-11, a topoisomerase I inhibitor. CPT-11 binds to topoisomerase I at the replication fork, creating a bulky adduct that is recognized as damaged DNA. When DNA damage was stimulated with CPT-11, protein expression of the nucleotide excision repair enzyme ERCC1 inversely correlated with cell viability, but not clonogenic survival. However, 4 out of the 6 TNBC cells were synergistically responsive by cell viability and 5 out of the 6 TNBC cells were synergistically responsive by clonogenic survival to the combination of ABT-888 and CPT-11. In vivo, the BRCA mutant cell line MX-1 treated with CPT-11 alone demonstrated significant decreased tumor growth; this decrease was enhanced further with the addition of ABT-888. Decrease in tumor growth correlated with an increase in double strand DNA breaks as measured by γ-H2AX phosphorylation. In summary, inhibiting two arms of the DNA repair pathway simultaneously in TNBC cell lines, independent of BRCA mutation status, resulted in un-repairable DNA damage and subsequent cell death.     

Checkpoint Kinase 1 (CHK1) Functions as Both a Diagnostic Marker and a Regulator of Epithelial-to-Mesenchymal Transition (EMT) in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is more difficult to treat and has a higher mortality rate than other subtypes. Although hormone receptor-targeted therapy is an effective treatment to increase survival rate in breast cancer patients, it is not suitable for TNBC patients. To address the issues, differentially expressed genes (DEGs) in TNBC patients from the Gene Expression Omnibus (GEO) database were analyzed. A total of 170 genes were obtained from three Genomic Spatial Events (GSEs) using the intersection of each GSE dataset and 61 DEGs were identified after validation with the gene enrichment analysis. We combined this with the degree scores from the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and protein-protein interaction (PPI) network, of which 7 genes were correlated with survival rate. Finally, a proteomics database revealed that only the CHK1 protein level was differently expressed in basal-like compared with other subtypes. We demonstrated that CHK1 expression was higher in TNBC cell lines compared with non-TNBC cell lines, and CHK1 promotes epithelial to mesenchymal transition (EMT) as well as migration and invasion ability. Our study provides new insight into the TNBC subnetwork that may be useful in the prognosis and treatment of TNBC patients.     

Highly Adaptable Triple-Negative Breast Cancer Cells as a Functional Model for Testing Anticancer Agents

A major obstacle in developing effective therapies against solid tumors stems from an inability to adequately model the rare subpopulation of panresistant cancer cells that may often drive the disease. We describe a strategy for optimally modeling highly abnormal and highly adaptable human triple-negative breast cancer cells, and evaluating therapies for their ability to eradicate such cells. To overcome the shortcomings often associated with cell culture models, we incorporated several features in our model including a selection of highly adaptable cancer cells based on their ability to survive a metabolic challenge. We have previously shown that metabolically adaptable cancer cells efficiently metastasize to multiple organs in nude mice. Here we show that the cancer cells modeled in our system feature an embryo-like gene expression and amplification of the fat mass and obesity associated gene FTO. We also provide evidence of upregulation of ZEB1 and downregulation of GRHL2 indicating increased epithelial to mesenchymal transition in metabolically adaptable cancer cells. Our results obtained with a variety of anticancer agents support the validity of the model of realistic panresistance and suggest that it could be used for developing anticancer agents that would overcome panresistance.     

Survival after Locoregional Recurrence or Second Primary Breast Cancer: Impact of the Disease-Free Interval

The association between the disease-free interval (DFI) and survival after a locoregional recurrence (LRR) or second primary (SP) breast cancer remains uncertain. The objective of this study is to clarify this association to obtain more information on expected prognosis. Women first diagnosed with early breast cancer between 2003–2006 were selected from the Netherlands Cancer Registry. LRRs and SP tumours within five years of first diagnosis were examined. The five-year period was subsequently divided into three equal intervals. Prognostic significance of the DFI on survival after a LRR or SP tumour was determined using Kaplan-Meier estimates and multivariable Cox regression analysis. Follow-up was complete until January 1, 2014. A total of 37,278 women was included in the analysis. LRRs or SP tumours were diagnosed in 890 (2,4%) and 897 (2,4%) respectively. Longer DFI was strongly and independently related to an improved survival after a LRR (long versus short: HR 0.65, 95% CI 0.48–0.88; medium versus short HR 0.81, 95% CI 0.65–1.01). Other factors related to improved survival after LRR were younger age (<70 years) and surgical removal of the recurrence. No significant association was found between DFI and survival after SP tumours. This is the first study to explore the association between the DFI and survival after recurrence in a nationwide population-based cancer registry. The DFI before a LRR is an independent prognostic factor for survival, with a longer DFI predicting better prognosis.     

三阴性乳腺癌靶向治疗相关信号通路及其临床应用

三阴性乳腺癌(triple negative breast cancer, TNBC)占全部乳腺癌病例的15%~20%,其雌激素受体、孕激素受体和人表皮生长因子受体2均为阴性表达,也是所有乳腺癌亚型中侵袭性和恶性程度较高的一种。TNBC还具有较高的复发风险和较差的预后特性。由于异质性高、临床特征复杂,化疗、放疗和手术切除等手段仍是当前TNBC治疗的主要方法。然而,严重的副作用、高复发风险和健康损伤等问题仍然不容忽视。随着TNBC基础研究的进展,越来越多的TNBC靶向治疗相关信号通路被揭示,而且其中有一部分已进入临床试验,为TNBC的治疗提供了充满希望和前景的分子靶点。此外,其中一些治疗靶点在TNBC精确分型和精准治疗的临床实践中发挥着重要的作用。本文对TNBC靶向治疗中经典的合成致死通路、PI3K/AKT/mTOR通路、PD-1/PD-L1免疫通路等信号通路及其临床试验进行了综述,同时介绍了近几年比较具有潜力的TNBC靶向治疗信号通路,包括肿瘤血管生成通路、多胺合成和分解代谢通路、SLC3A2/LAT1通路以及IGF-1/IGF-1R/FAK/YAP信号转导通路等。