Multi-instance Multi-task Learning for Joint Clinical Outcome and Genomic Profile Predictions from the Histopathological Images.

With the remarkable success of digital histopathology and the deep learning technology, many whole-slide pathological images (WSIs) based deep learning models are designed to help pathologists diagnose human cancers. Recently, rather than predicting categorical variables as in cancer diagnosis, several deep learning studies are also proposed to estimate the continuous variables such as the patients' survival or their transcriptional profile. However, most of the existing studies focus on conducting these predicting tasks separately, which overlooks the useful intrinsic correlation among them that can boost the prediction performance of each individual task. In addition, it is sill challenge to design the WSI-based deep learning models, since a WSI is with huge size but annotated with coarse label. In this study, we propose a general multi-instance multi-task learning framework (HistMIMT) for multi-purpose prediction from WSIs. Specifically, we firstly propose a novel multi-instance learning module (TMICS) considering both common and specific task information across different tasks to generate bag representation for each individual task. Then, a soft-mask based fusion module with channel attention (SFCA) is developed to leverage useful information from the related tasks to help improve the prediction performance on target task. We evaluate our method on three cancer cohorts derived from the Cancer Genome Atlas (TCGA). For each cohort, our multi-purpose prediction tasks range from cancer diagnosis, survival prediction and estimating the transcriptional profile of gene TP53. The experimental results demonstrated that HistMIMT can yield better outcome on all clinical prediction tasks than its competitors.

The heterogeneity of tumour immune microenvironment revealing the CRABP2/CD69 signature discriminates distinct clinical outcomes in breast cancer.

BACKGROUND: It has been acknowledged that the tumour immune microenvironment (TIME) plays a critical role in determining therapeutic responses and clinical outcomes in breast cancer (BrCa). Thus, the identification of the TIME features is essential for guiding therapy and prognostic assessment for BrCa. METHODS: The heterogeneous cellular composition of the TIME in BrCa by single-cell RNA sequencing (scRNA-seq). Two subtype-special genes upregulated in the tumour-rich subtype and the immune-infiltrating subtype were extracted, respectively. The CRABP2/CD69 signature was established based on CRABP2 and CD69 expression, and its predictive values for the clinical outcome and the neoadjuvant chemotherapy (NAT) responses were validated in multiple cohorts. Moreover, the oncogenic role of CRABP2 was explored in BrCa cells. RESULTS: Based on the heterogeneous cellular composition of the TIME in BrCa, the BrCa samples could be divided into the tumour-rich subtype and the immune-infiltrating subtype, which exhibited distinct prognosis and chemotherapeutic responses. Next, we extracted CRABP2 as the biomarker for the tumour-rich subtype and CD69 as the biomarker for the immune-infiltrating subtype. Based on the CRABP2/CD69 signature, BrCa samples were re-divided into three subtypes, and the CRABP2highCD69low subtype exhibited the worst prognosis and the lowest chemotherapeutic response, while the CRABP2lowCD69high subtype showed the opposite results. Furthermore, CARBP2 functioned as a novel oncogene in BrCa, which promoted tumour cell proliferation, migration, and invasion, and CRABP2 inhibition triggered the activation of cytotoxic T lymphocytes (CTLs). CONCLUSION: The CRABP2/CD69 signature is significantly associated with the TIME features and could effectively predict the clinical outcome. Also, CRABP2 is determined to be a novel oncogene, which could be a therapeutic target in BrCa.

Single-cell transcriptome analysis indicates fatty acid metabolism-mediated metastasis and immunosuppression in male breast cancer.

Male breast cancer (MBC) is a rare but aggressive malignancy with cellular and immunological characteristics that remain unclear. Here, we perform transcriptomic analysis for 111,038 single cells from tumor tissues of six MBC and thirteen female breast cancer (FBC) patients. We find that that MBC has significantly lower infiltration of T cells relative to FBC. Metastasis-related programs are more active in cancer cells from MBC. The activated fatty acid metabolism involved with FASN is related to cancer cell metastasis and low immune infiltration of MBC. T cells in MBC show activation of p38 MAPK and lipid oxidation pathways, indicating a dysfunctional state. In contrast, T cells in FBC exhibit higher expression of cytotoxic markers and immune activation pathways mediated by immune-modulatory cytokines. Moreover, we identify the inhibitory interactions between cancer cells and T cells in MBC. Our study provides important information for understanding the tumor immunology and metabolism of MBC.

Feasibility and efficacy of ultrasound-guided high-intensity focused ultrasound of breast fibroadenoma.

OBJECTIVE: This nonrandomized prospective clinical trial aimed to assess the efficacy, safety and follow-up outcomes of ultrasound-guided high-intensity focused ultrasound (USgHIFU) surgery in patients with breast fibroadenoma. METHODS: With the approval of the institutional ethics committee and written informed consent, a total of 113 patients diagnosed with breast fibroadenoma by core-needle biopsy in our hospital were recruited. USgHIFU surgery was performed under local anesthesia. Contrast-enhanced ultrasound (CEUS) or contrast-enhanced MRI (CEMRI) was performed to evaluate the nonperfused volume (NPV). The patients were followed up with physical examination and ultrasound imaging. RESULTS: The clinical outcome of 85 patients with 147 fibroadenomas with a follow-up time of more than 3 months was analyzed in this study. Fifty-two patients had one lesion, twenty-one patients had two lesions and twelve patients had more than two lesions. During USgHIFU, the median localization time for all fibroadenomas was 3 (interquartile range: 1, 5) min, and the median treatment time was 9 (interquartile range: 5, 15) min. Under local anesthesia, all the patients tolerated the treatment well. No serious epidermal burns were observed in any of the patients. Based on CEUS or CEMRI imaging evaluation, the median NPV ratio was 100% (interquartile range: 79.2%, 116.8%). The VRR were 26.77 ± 50.05%, 50.22 ± 42.01% and 72.74 ± 35.39% at 3-6 months, 6-12 months and >12 months, respectively, which showed significant statistical difference (p < .001). CONCLUSION: Ultrasound-guided HIFU surgery is an effective and safe noninvasive alternative technique for the treatment of breast fibroadenoma.

An inflammatory-related genes signature based model for prognosis prediction in breast cancer.

Background: Breast cancer has become the most common malignant tumor in the world. It is vital to discover novel prognostic biomarkers despite the fact that the majority of breast cancer patients have a good prognosis because of the high heterogeneity of breast cancer, which causes the disparity in prognosis. Recently, inflammatory-related genes have been proven to play an important role in the development and progression of breast cancer, so we set out to investigate the predictive usefulness of inflammatory-related genes in breast malignancies. Methods: We assessed the connection between Inflammatory-Related Genes (IRGs) and breast cancer by studying the TCGA database. Following differential and univariate Cox regression analysis, prognosis-related differentially expressed inflammatory genes were estimated. The prognostic model was constructed through the Least Absolute Shrinkage and Selector Operation (LASSO) regression based on the IRGs. The accuracy of the prognostic model was then evaluated using the Kaplan-Meier and Receiver Operating Characteristic (ROC) curves. The nomogram model was established to predict the survival rate of breast cancer patients clinically. Based on the prognostic expression, we also looked at immune cell infiltration and the function of immune-related pathways. The CellMiner database was used to research drug sensitivity. Results: In this study, 7 IRGs were selected to construct a prognostic risk model. Further research revealed a negative relationship between the risk score and the prognosis of breast cancer patients. The ROC curve proved the accuracy of the prognostic model, and the nomogram accurately predicted survival rate. The scores of tumor-infiltrating immune cells and immune-related pathways were utilized to calculate the differences between the low- and high-risk groups, and then explored the relationship between drug susceptibility and the genes that were included in the model. Conclusion: These findings contributed to a better understanding of the function of inflammatory-related genes in breast cancer, and the prognostic risk model provides a potentially promising prognostic strategy for breast cancer.

Heterogeneous circulating tumor cells correlate with responses to neoadjuvant chemotherapy and prognosis in patients with locally advanced breast cancer.

Neoadjuvant chemotherapy (NCT) is the standard treatment for patients with locally advanced breast cancer (LABC). The predictive value of heterogeneous circulating tumor cells (CTCs) in NCT response has not been determined. All patients were staged as LABC, and blood samples were collected at the time of biopsy, and after the first and eighth NCT courses. Patients were divided into High responders (High-R) and Low responders (Low-R) according to Miller-Payne system and changes in Ki-67 levels after NCT treatment. A novel SE-i·FISH strategy was applied to detect CTCs. Heterogeneities were successfully analyzed in patients undergoing NCT. Total CTCs increased continuously and were higher in Low-R group, while in High-R group, CTCs increased slightly during NCT before returning to baseline levels. Triploid and tetraploid chromosome 8 increased in Low-R but not High-R group. The number of small CTCs in Low-R group increased significantly until the last sample, however, remained constant in High-R group. The patients with more CTCs had shorter PFS and OS than those with less CTCs after the eighth course of NCT. Total CTCs following NCT could predict patients' responses. More detailed characterizations of CTC blood profiles may improve predictive capacity and treatments of LABC.

Awakening Allies for Breaking Microenvironment Barriers: NIR-II Guided Orthogonal Activation of Tumor-Infiltrating Mast Cells for Efficient Nano-Drug Delivery.

Mast cells (MCs), powerful immune cells that heavily infiltrate cancer cells, play a crucial role in tumor formation. Activated MCs can release histamine and a family of proteases through degranulation effects, concurrently achieving endothelial junction weakening and stromal degradation of the tumor microenvironment, thereby clearing the obstacles for nano-drug infiltration. To achieve precise activation of tumor-infiltrating MCs, orthogonally excited rare earth nanoparticles (ORENP), with two channels, are introduced for the controllable stimulating drugs release wrapped in "photocut tape". The ORENP can emit near-infrared II (NIR-II) for image tracing for tumor localization in Channel 1 (808/NIR-II) and allows energy upconversion to emit ultraviolet (UV) light for releasing drugs for MCs stimulation in Channel 2 (980/UV). Finally, the combined use of chemical and cellular tools enables clinical nano-drugs to achieve a significant increase in tumor infiltration, thereby enhancing the efficacy of nano-chemotherapy.

miR-1275 targets MDK/AKT signaling to inhibit breast cancer chemoresistance by lessening the properties of cancer stem cells.

Chemoresistance is a major obstacle in the neoadjuvant chemotherapy (NCT) of locally advanced breast cancer (LABC). Identification of miRNAs as prognostic biomarkers may help overcome chemoresistance of breast cancer (BC). This study aimed to evaluate the expression level of miR-1275 in plasma samples and its biological functions in the chemoresistance of BC. The expression levels of miR-1275 in plasma samples and cells were measured by RT-qPCR. CRISPR/Cas9-mediated gene editing was used to construct miR-1275 knock-out cells in MCF-7. We found that miR-1275 was significantly downregulated in plasma from patients resistant to chemotherapy and in chemoresistant BC cell lines, while patients with low levels of miR-1275 showed poor overall survival. miR-1275 knock-out promoted chemoresistance in BC cells by increasing the properties of cancer stem cells (CSCs). Mechanistically, we identified that MDK was determined to be direct downstream protein of miR-1275 which initiated PI3K/Akt signaling in breast cancer cells. We demonstrated that the high expression level of miR-1275 in plasma predicted better response to NCT. The reduction of miR-1275 promoted BC cells chemoresistance by increasing CSCs properties via targeting MDK/AKT axis. The potential of miR-1275 as a new prognostic biomarker and therapeutic target of BC patients was identified.

Value of negatively correlated miR-205-5p/HMGB3 and miR-96-5p/FOXO1 on the diagnosis of breast cancer and benign breast diseases.

Background: MicroRNA (miRNA) and mRNA levels in matching specimens were used to identify miRNA-mRNA interactions. We aimed to integrate transcriptome, immunophenotype, methylation, mutation, and survival data analyses to examine the profiles of miRNAs and target mRNAs and their associations with breast cancer (BC) diagnosis. Methods: Based on the Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA), differentially expressed miRNAs and targeted mRNAs were screened from experimentally verified miRNA-target interaction databases using Pearson's correlation analysis. We used real-time quantitative reverse transcription polymerase chain reaction to verify BC and benign disease samples, and logistic regression analysis was used to establish a diagnostic model based on miRNAs and target mRNAs. Receiver operating characteristic curve analysis was performed to test the ability to recognize the miRNA-mRNA pairs. Next, we investigated the complex interactions between miRNA-mRNA regulatory pairs and phenotypic hallmarks. Results: We identified 27 and 359 dysregulated miRNAs and mRNAs, respectively, based on the GEO and TCGA databases. Using Pearson's correlation analysis, 10 negative miRNA-mRNA regulatory pairs were identified after screening both databases, and the related miRNA and target mRNA levels were assessed in 40 BC tissues and 40 benign breast disease tissues. Two key regulatory pairs (miR-205-5p/High mobility group box 3 (HMGB3) and miR-96-5p/Forkhead Box O1 (FOXO1)) were selected to establish the diagnostic model. They also had utility in survival and clinical analyses. Conclusions: A diagnostic model including two miRNAs and their respective target mRNAs was established to distinguish between BC and benign breast diseases. These markers play essential roles in BC pathogenesis.

LnNP@ZIF8 Smart System for In Situ NIR-II Ratiometric Imaging-Based Tumor Drug Resistance Evaluation.

Just-in-time evaluation of drug resistance in situ will greatly facilitate the achievement of precision cancer therapy. The rapid elevation of reactive oxygen species (ROS) is the key to chemotherapy. Hence, suppressed ROS production is an important marker for chemotherapy drug resistance. Herein, a NIR-II emission smart nanoprobe (LnNP@ZIF8, consisting of a lanthanide-doped nanoparticle (LnNP) core and metal-organic framework shell (ZIF8)) is constructed for drug delivery and in vivo NIR-II ratiometric imaging of ROS for tumor drug resistance evaluation. The drug-loaded nanoprobes release therapeutic substances for chemotherapy in the acidic tumor tissue. As the level of ROS increases, the LnNPs shows responsively descending fluorescence intensity at 1550 nm excited by 980 nm (F1550, 980Ex), while the fluorescence of the LnNPs at 1060 nm excited by 808 nm (F1060, 808Ex) is stable. Due to the ratiometric F1550, 980Ex/F1060, 808Ex value exhibiting a linear relationship with ROS concentration, NIR-II imaging results of ROS change based on this ratio can be an important basis for determining tumor drug resistance. As the chemotherapy and resistance evaluation are explored continuously in situ, the ratiometric imaging identifies drug resistance successfully within 24 h, which can greatly improve the timeliness of accurate treatment.

Angiotensin-converting enzyme 2 identifies immuno-hot tumors suggesting angiotensin-(1-7) as a sensitizer for chemotherapy and immunotherapy in breast cancer.

BACKGROUND: Angiotensin-converting enzyme 2 (ACE2) is known as a tumor suppressor and lowly expressed in most cancers. The expression pattern and role of ACE2 in breast cancer (BC) have not been deeply elucidated. METHODS: A systematic pan-cancer analysis was conducted to assess the expression pattern and immunological role of ACE2 based on RNA-sequencing (RNA-seq) data downloaded from The Cancer Genome Atlas (TCGA). The correlation of ACE2 expression and immunological characteristics in the BC tumor microenvironment (TME) was evaluated. The role of ACE2 in predicting the response to therapeutic options was estimated. Moreover, the pharmacodynamic effect of angiotensin-(1-7) (Ang-1-7), the product of ACE2, on chemotherapy and immunotherapy was evaluated on the BALB/c mouse BC model. In addition, the plasma samples from BC patients receiving neoadjuvant chemotherapy were collected and subjected to the correlation analysis of the expression level of Ang-1-7 and the response to neoadjuvant chemotherapy. RESULTS: ACE2 was lowly expressed in BC tissues compared with that in adjacent tissues. Interestingly, ACE2 was shown the highest correlation with immunomodulators, tumor-infiltrating immune cells (TIICs), cancer immunity cycles, immune checkpoints, and tumor mutation burden (TMB) in BC. In addition, a high level of ACE2 indicated a low response to endocrine therapy and a high response to chemotherapy, anti-ERBB therapy, antiangiogenic therapy and immunotherapy. In the mouse model, Ang-1-7 sensitized mouse BC to the chemotherapy and anti-PD-1 immunotherapy, which revealed its significant anti-tumor effect. Moreover, a high plasma level of Ang-1-7 was associated with a better response to neoadjuvant chemotherapy. CONCLUSIONS: ACE2 identifies immuno-hot tumors in BC, and its enzymatic product Ang-1-7 sensitizes BC to the chemotherapy and immunotherapy by remodeling the TME.

Evaluating the learning curve of high intensity focus ultrasound for breast fibroadenoma by CUSUM analysis: a multi-center study.

OBJECTIVE: To explore the learning curve of high intensity focus ultrasound (HIFU) treatment for breast fibroadenoma. METHODS: A database of 110 patients with 255 breast fibroadenomas who underwent HIFU treatment at two different clinical centers (Center 1 and 2) were retrospectively analyzed. The learning curves of HIFU treatment for breast fibroadenoma were drawn by CUSUM analysis in two centers, respectively. According to the inflection point of the learning curves, the treatment was divided into two groups: initial phase and consolidation phase. HIFU treatment parameters were compared between two groups. The effectiveness and safety results were also evaluated. RESULTS: The inflection points of the learning curves were the 60th treatment in Center 1 and the 65th treatment in Center 2. The screening time, treatment time, sonication time and hyperechoic scale change time were significantly shorter in consolidation phase than those in initial phase of the two centers (p < 0.05). There were no differences in non-perfused volume (NPV) ratio and energy effect factor (EEF) between the two groups in Center 1, while in Center 2, these above-mentioned results in consolidation phase led to a greater improvement than those in initial phase. There was no difference of Visual Analogue Scale (VAS) scores and no adverse event observed in both centers. CONCLUSION: HIFU treatment for breast fibroadenoma was effective and safe. The learning curve of HIFU treatment for breast fibroadenoma can be completed after treating 60-65 tumors without increasing the safety risk.

High FLT3 expression indicates favorable prognosis and correlates with clinicopathological parameters and immune infiltration in breast cancer.

Purpose: Breast cancer is a highly heterogeneous malignancy, seriously threatening female health worldwide and inducing higher mortalities. Few have the studies evaluated Fms-like TyrosineKinase-3 (FLT3) in prognostic risk, immunotherapy or any other treatment of breast cancer. Our study focused on investigating the function of FLT3 in breast cancer. Patients and methods: Based on transcriptome and methylation data mined from The Cancer Gene Atlas (TCGA), we explored the clinical features of FLT3 expression in 1079 breast cancer samples. RT-qPCR in cell lines and tissue samples was used to verify the expression difference of FLT3. Kaplan-Meier survival analysis and cox regression models were employed for screening of FLT3 with potential prognostic capacity. Subsequently, functional analysis of the co-expressed genes was conducted using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene-set enrichment analysis (GSEA). The correlation between FLT3 expression and tumor immune infiltration was jointly analyzed with estimate, ssGSEA, TIMER, and TISIDB. Then we employed checkpoint-related molecules, immunophenoscore (IPS), and tumor mutation burden (TMB) to assess the efficacy of immuno-checkpoint inhibitors (ICIs). Pearson correlation coefficient was employed to exam the association between DNA methylation and FLT3 expression. Results: FLT3 displays an elevated expression in breast cancer than normal pairs and is significantly associated with multiple clinical characteristics like age, menopause status, histological type, pathological stage, and molecular subtype as well as increased overall survival (OS). Additionally, FLT3 is a favorable independent prognostic factor. GO, KEGG, and GSEA suggested that FLT3 was associated with diversified immune-related features. FLT3 expression is correlated with the abundance of various immune cells namely CD4+T cell, CD8+ T cell, myeloid dendritic cell, and neutrophil as well as immune inhibitors especially CTLA4, which is positively correlated with FLT3 expression. Moreover, TMB displayed a negative correlation with FLT3 expression while IPS showed adverse tendency. Ultimately, the methylation of FLT3 downregulates the gene expression and closely binds to a few clinical parameters. Conclusion: FLT3 can be used for prognostic prediction and is relevant to immune infiltration in breast cancer. FLT3 may pave the way for future novel immunotherapies.

RUNX regulated immune-associated genes predicts prognosis in breast cancer.

Background: Breast cancer is the most common malignant tumor in women. RUNX family has been involved in the regulation of different carcinogenic processes and signaling pathways with cancer, which is closely related to immunity and prognosis of various tumors, and also plays an important role in the development and prognosis of breast cancer. Methods: We discovered the expression of RUNX family through GEPIA Dataset and then evaluated the relationship between RUNX family and immune-related genes and the prognosis of breast cancer through analyzing TCGA database. A prognostic model was established and verified via cox proportional hazards regression model using R packages. We evaluated the accuracy of the prognostic model by Kaplan-Meier curves and receiver operating characteristic (ROC) curves. Additionally, we obtained the relationship between the RUNX family and immune infiltration by TIMER database. Finally, the dual luciferase reporter assay was used to verify the regulation of RUNX3 on potential target genes ULBP2 and TRDV1, and the effects of ULBP2 and TRDV1 on the growth of breast cancer cells were explored by CCK-8, colony formation and wound healing assays. Results: We screened out RUNX family-regulated immune-related genes associated with the prognosis of breast cancer. These predictors included PSME2, ULBP2, IL-18, TSLP, NPR3, TRDV1. Then a prognosis-related risk score model was built using the independent risk factors to provide a clinically appropriate method predicting the overall survival (OS) probability of the patients with breast cancer. In addition, a further research was made on the functions of high risk immune gene ULBP2 and low risk immune gene TRDV1 which regulated by RUNX3, the results showed that down-regulation of ULBP2 suppressed breast cancer cell proliferation and TRDV1 had the opposite functions. The prognostic model we constructed could promote the development of prognostic, and was associated with lower immune infiltration. Conclusion: The expression of RUNX family was closely related to the prognosis of breast cancer. At the same time, RUNX family could modulate the functions of immune-related genes, and affect the development and prognosis of breast cancer. These immune-related genes regulated by RUNX family could be promising prognostic biomarkers and therapeutic targets in breast cancer.

Ultrasound radiomics features predicting the dosimetry for focused ultrasound surgery of benign breast tumor: A retrospective study.

Purpose: To investigate the correlation between pre-ablation ultrasound radiomics features and the sonication energy for focused ultrasound surgery (FUS) of benign breast tumors. Method: 53 benign breast tumors of 28 patients treated by ultrasound-guided focused ultrasound surgery (USgFUS) were included in this study. The sonication energy per unit volume of each tumor was calculated. Three-quarter point was chosen as the cut-off to divide the 53 included tumors into high sonication energy (HSE, n = 14) and low sonication energy (LSE, n = 39) groups. For each tumor, the region of interest (ROI) of both the tumor itself (tROI) and the near field tissue (nfROI) were delineated and analyzed separately using ImageJ software. Pearson correlation coefficient and multiple linear regression analysis were used for radiomics feature selection. To explore the diagnostic performance of different ultrasound radiomics features, a receiver operating characteristic (ROC) curve analysis was performed. Results: In total of 68 radiomics features were extracted from pre-ablation ultrasound images of each tumor. Of all radiomics features, BX in tROI (p < 0.001), BX (p = 0.001) and Circ (p = 0.019) in nfROI were independently predictive features of sonication energy per unit volume. The ROC curves showed that the area under the curve (AUC) values of BX in tROI, BX, and Circ in nfROI were 0.797, 0.787 and 0.822, respectively. Conclusion: This study provided three radiomics features of pre-ablation ultrasound image as predictors of sonication dose for FUS in benign breast tumors. Further clinical trials are needed to confirm the predictive effect of these radiomics features.

Radiogenomics analysis reveals the associations of dynamic contrast-enhanced-MRI features with gene expression characteristics, PAM50 subtypes, and prognosis of breast cancer.

Background: To investigate reliable associations between dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) features and gene expression characteristics in breast cancer (BC) and to develop and validate classifiers for predicting PAM50 subtypes and prognosis from DCE-MRI non-invasively. Methods: Two radiogenomics cohorts with paired DCE-MRI and RNA-sequencing (RNA-seq) data were collected from local and public databases and divided into discovery (n = 174) and validation cohorts (n = 72). Six external datasets (n = 1,443) were used for prognostic validation. Spatial-temporal features of DCE-MRI were extracted, normalized properly, and associated with gene expression to identify the imaging features that can indicate subtypes and prognosis. Results: Expression of genes including RBP4, MYBL2, and LINC00993 correlated significantly with DCE-MRI features (q-value < 0.05). Importantly, genes in the cell cycle pathway exhibited a significant association with imaging features (p-value < 0.001). With eight imaging-associated genes (CHEK1, TTK, CDC45, BUB1B, PLK1, E2F1, CDC20, and CDC25A), we developed a radiogenomics prognostic signature that can distinguish BC outcomes in multiple datasets well. High expression of the signature indicated a poor prognosis (p-values < 0.01). Based on DCE-MRI features, we established classifiers to predict BC clinical receptors, PAM50 subtypes, and prognostic gene sets. The imaging-based machine learning classifiers performed well in the independent dataset (areas under the receiver operating characteristic curve (AUCs) of 0.8361, 0.809, 0.7742, and 0.7277 for estrogen receptor (ER), human epidermal growth factor receptor 2 (HER2)-enriched, basal-like, and obtained radiogenomics signature). Furthermore, we developed a prognostic model directly using DCE-MRI features (p-value < 0.0001). Conclusions: Our results identified the DCE-MRI features that are robust and associated with the gene expression in BC and displayed the possibility of using the features to predict clinical receptors and PAM50 subtypes and to indicate BC prognosis.

Dosimetric analysis of ultrasound-guided high intensity focused ultrasound ablation for breast fibroadenomas: a retrospective study.

OBJECTIVE: To investigate the factors influencing the sonication dosage and efficiency of ultrasound-guided high intensity focused ultrasound (USgHIFU) for breast fibroadenomas. MATERIALS AND METHODS: Forty-nine patients with 78 breast fibroadenomas who underwent USgHIFU were retrospectively analyzed. The energy efficiency factor (EEF) was set as dependent variable, and the factors possibly influencing the sonication dosage, including age, body mass index (BMI), fibroadenoma size, distance from the shallow margin of the fibroadenoma to skin, distance from the deep margin of the fibroadenoma to pectoralis major, types of near field acoustic pathway, and Adler blood flow classification of ultrasound, were set as independent variables. The correlation between EEF and these independent variables were analyzed, and an optimal scaling regression model was established. RESULTS: Fibroadenoma size, distance from the shallow margin of the fibroadenoma to skin and type of near field acoustic pathway had significant correlation with EEF (p < 0.05). An EEF (y) dosimetry model of y= -0.496X1 + 0.287X2 + 0.203X3 was established, in which X1 stands for size of fibroadenoma, X2 stands for the distance from shallow margin of the fibroadenoma to skin, and X3 stands for type of near field acoustic pathway. The predicted EEF value was significantly related to actual EEF (R = 0.698, p = 0.000). CONCLUSIONS: Fibroadenoma size, distance from the shallow margin of the fibroadenoma to skin and type of near field acoustic pathway could be used as predictors to evaluate the dosage delivery of USgHIFU treatment for breast fibroadenomas.

Circulating tumor cells may serve as a supplement to RECIST in neoadjuvant chemotherapy of patients with locally advanced breast cancer.

BACKGROUND: Circulating tumor cells (CTCs) have been shown to be associated with the response to neoadjuvant chemotherapy (NCT) and the prognosis of locally advanced breast cancer (LABC) patients. Our study aimed to investigate whether the change of CTC status during NCT could serve as a supplement to the Response Evaluation Criteria in Solid Tumors (RECIST) in the treatment and evaluation of LABC patients. METHODS: 6 ml of blood samples were collected before NCT, after the first cycle of NCT and after the completion of NCT, respectively. According to the change of CTC number during NCT, the patients were divided into "CTC low-response (low-R)" group and "CTC high-response (high-R)" group. Survival data of each group of patients were obtained through long-term follow-up. RESULTS: A total of 35 patients diagnosed with LABC were enrolled. The median follow-up for distant metastasis was 27 months (range 7-36 months). There was no significant difference in distant metastasis-free survival (DMFS) between PR/CR group and PD/SD group (P = 0.0914), while CTC low-R group had a worse DMFS than CTC high-R group (P = 0.0199). In PR/CR subgroup, patients with CTC low-R showed a lower DMFS compared with those with CTC high-R (P = 0.0159). However, in PD/SD subgroup, there was no significant difference in DMFS between CTC low-R and CTC high-R group (P = 0.7521). In terms of assessing response to NCT, CTC change or RECIST classification alone had an AUC of 0.533 (95% CI 0.277-0.790) and 0.700 (95% CI 0.611-0.789), respectively. When combining the two, the AUC slightly increased to 0.713 (95% CI 0.532-0.895). CONCLUSION: The change of CTC number during NCT has a potential to serve as a supplement to RECIST in the assessment of NCT efficacy and the prognosis of LABC patients.

Diagnostic value of oncofetal miRNAs in cancers: A comprehensive analysis of circulating miRNAs in pan-cancers and UCB.

BACKGROUND: Circulating miRNAs are promising biomarkers for detection of various cancers. As a "developmental" disorder, cancer showed great similarities with embryos. OBJECTIVE: A comprehensive analysis of circulating miRNAs in umbilical cord blood (UCB) and pan-cancers was conducted to identify circulating miRNAs with potential for cancer detection. METHODS: A total of 3831 cancer samples (2050 serum samples from 15 types of cancers and 1781 plasma samples from 13 types of cancers) and 248 UCB samples (120 serum and 128 plasma samples) with corresponding NCs from Chinese populations were analyzed via consistent experiment workflow with Exiqon panel followed by multiple-stage validation with qRT-PCR. RESULTS: Thirty-four serum and 32 plasma miRNAs were dysregulated in at least one type of cancer. Eighteen serum and 16 plasma miRNAs were related with embryos. Among them, 9 serum and 8 plasma miRNAs with consistent expression patterns between pan-cancers and UCB were identified as circulating oncofetal miRNAs. Retrospective analysis confirmed the diagnostic ability of circulating oncofetal miRNAs for specific cancers. And the oncofetal miRNAs were mainly up-regulated in tissues of pan-cancers. CONCLUSIONS: Our study might serve as bases for the potential application of the non-invasive biomarkers in the future clinical.

Preoperative ultrasound-based radiomics score can improve the accuracy of the Memorial Sloan Kettering Cancer Center nomogram for predicting sentinel lymph node metastasis in breast cancer.

PURPOSE: To develop a combined nomogram by incorporating the Memorial Sloan Kettering Cancer Center (MSKCC) nomogram and ultrasound (US)-based radiomics score (Radscore) for predicting sentinel lymph node (SLN) metastasis in invasive breast cancer. MATERIALS AND METHODS: This retrospective study was approved by the ethics committee of our institution, and written informed consent was waived. A total of 452 patients with invasive breast cancer who received SLN Biopsy in a single center were included between January 2016 and December 2019. The patients were divided into a training set (n = 318) and a validation set (n = 134). A total of 1216 features were extracted from the regions of interest (ROIs) of the tumors on conventional ultrasound. The maximum relevance minimum redundancy (mRMR) and the least absolute shrinkage and selection operator (LASSO) algorithm were used to build the Radscore. Afterward, the diagnostic performance was assessed and validated. Comparison of receiver operating characteristic (ROC) curves and decision curve analysis (DCA) were performed to evaluate the incremental value of the combined model. RESULTS: Obtained from 18 features, the Radscore indicated a favorable discriminatory capability in the training set with an area under the curve (AUC) of 0.834, whereas a value of 0.770 was observed in the validation set. The AUC of the combined model was 0.901 (95 % confidence interval (95 % CI): 0.865-0.938) in the training set and 0.833 (95 % CI: 0.788-0.878) in the validation set. Both of them were superior to MSKCC or imaging Radscore alone (P < 0.05). DCA demonstrated that the combined model was superior to the others in terms of clinical practicability. CONCLUSION: Preoperative US-based Radscore can improve the accuracy of clinical MSKCC nomogram for SLN metastasis prediction in breast cancer.