Contrast Enhancement on Cone-Beam Breast-CT for Discrimination of Breast Cancer Immunohistochemical Subtypes

PURPOSE: To evaluate whether contrast enhancement on cone-beam breast-CT (CBBCT) could aid in discrimination of breast cancer subtypes and receptor status. METHODS: This study included female patients age >40 years with malignant breast lesions identified on contrast-enhanced CBBCT. Contrast enhancement of malignant breast lesions was standardized to breast fat tissue contrast enhancement. All breast lesions were approved via image-guided biopsy or surgery. Immunohistochemical staining was conducted for expression of estrogen (ER), progesterone (PR), human epidermal growth factor receptor-2 (HER2) and Ki-67 index. Contrast enhancement of breast lesions was correlated with immunohistochemical breast cancer subtypes (Luminal A, Luminal B, HER2 positive, triple negative), receptor status and Ki-67 expression. RESULTS: Highest contrast enhancement was seen for Luminal A lesions (93.6 HU) compared to Luminal B lesions (47.6 HU, P = .002), HER2 positive lesions (83.5 HU, P = .359) and triple negative lesions (45.3 HU, P = .005). Contrast enhancement of HER2 positive lesions was higher than Luminal B lesions (P = .044) and triple negative lesions (P = .039). No significant difference was evident between Luminal B and triple negative lesions (P = .439). Lesions with high Ki-67 index showed lower contrast enhancement than those with low Ki-67 index (P = .0043). ER, PR and HER2 positive lesions demonstrated higher contrast enhancement than their receptor negative counterparts, although differences did not reach statistical significance (P = .1714; P = .3603; P = .2166). CONCLUSIONS: Contrast enhancement of malignant breast lesions on CBBCT correlates with immunohistochemical subtype and proliferative potential. Thereby, CBBCT might aid in selecting individualized treatment strategies for breast cancer patients based on pre-operative imaging.     

Increased MAPK1/3 Phosphorylation in Luminal Breast Cancer Related with PIK3CA Hotspot Mutations and Prognosis

INTRODUCTION: While mutations in PIK3CA are most frequently (45%) detected in luminal breast cancer, downstream PI3K/AKT/mTOR pathway activation is predominantly observed in the basal subtype. The aim was to identify proteins activated in PIK3CA mutated luminal breast cancer and the clinical relevance of such a protein in breast cancer patients. MATERIALS AND METHODS: Expression levels of 171 signaling pathway (phospho-)proteins established by The Cancer Genome Atlas (TCGA) using reverse phase protein arrays (RPPA) were in silico examined in 361 breast cancers for their relation with PIK3CA status. MAPK1/3 phosphorylation was evaluated with immunohistochemistry on tissue microarrays (TMA) containing 721 primary breast cancer core biopsies to explore the relationship with metastasis-free survival. RESULTS: In silico analyses revealed increased phosphorylation of MAPK1/3, p38 and YAP, and decreased expression of p70S6K and 4E–BP1 in PIK3CA mutated compared to wild-type luminal breast cancer. Augmented MAPK1/3 phosphorylation was most significant, i.e. in luminal A for both PIK3CA exon 9 and 20 mutations and in luminal B for exon 9 mutations. In 290 adjuvant systemic therapy naïve lymph node negative (LNN) breast cancer patients with luminal cancer, high MAPK phosphorylation in nuclei (HR = 0.49; 95% CI, 0.25–0.95; P = .036) and in tumor cells (HR = 0.37; 95% CI, 0.18–0.79; P = .010) was related with favorable metastasis-free survival in multivariate analyses including traditional prognostic factors. CONCLUSION: Enhanced MAPK1/3 phosphorylation in luminal breast cancer is related to PIK3CA exon-specific mutations and correlated with favorable prognosis especially when located in the nuclei of tumor cells.     

A Long Noncoding RNA Signature That Predicts Pathological Complete Remission Rate Sensitively in Neoadjuvant Treatment of Breast Cancer

BACKGROUND: Mounting evidence suggests that long noncoding RNAs (lncRNAs) are closely related to pathological complete response (pCR) in neoadjuvant treatment of breast cancer. Here, we construct lncRNA associated models to predict pCR rate. METHODS: LncRNA expression profiles of breast cancer patients treated with neoadjuvant chemotherapy (NAC) were obtained from Gene Expression Omnibus by repurposing existing microarray data. The prediction model was firstly built by analyzing the correlation between pCR and lncRNA expression in the discovery dataset GSE 25066 (n = 488). Another three independent datasets, GSE20194 (n = 278), GSE20271 (n = 178), and GSE22093 (n = 97), were integrated as the validation cohort to assess the prediction efficiency. RESULTS: A novel lncRNA signature (LRS) consisting of 36 lncRNAs was identified. Based on this LRS, patients with NAC treatment were divided into two groups: LRS-high group and LRS-low group, with positive correlation of pCR rate in the discovery dataset. In the validation cohort, univariate and multivariate analyses both demonstrated that high LRS was associated with higher pCR rate. Subgroup analysis confirmed that this model performed well in luminal B [odds ratio (OR) = 5.4; 95% confidence interval (CI) = 2.7-10.8; P = 1.47e-06], HER2-enriched (OR = 2.5; 95% CI = 1.1-5.7; P = .029), and basal-like (OR = 5.5; 95% CI = 2.3-16.2; P = 5.32e-04) subtypes. Compared with other preexisting prediction models, LRS demonstrated better performance with higher area under the curve. Functional annotation analysis suggested that lncRNAs in this signature were mainly involved in cancer proliferation process. CONCLUSION: Our findings indicated that our lncRNA signature was sensitive to predict pCR rate in the neoadjuvant treatment of breast cancer, which deserves further evaluation.     

Predicting Treatment Response of Breast Cancer to Neoadjuvant Chemotherapy Using Ultrasound-Guided Diffuse Optical Tomography

PURPOSE: To prospectively investigate ultrasound-guided diffuse optical tomography (US-guided DOT) in predicting breast cancer response to neoadjuvant chemotherapy (NAC). MATERIALS AND METHODS: Eighty-eight breast cancer patients, with a total of 93 lesions, were included in our study. Pre– and post–last chemotherapy, size and total hemoglobin concentration (THC) of each lesion were measured by conventional US and US-guided DOT 1 day before biopsy (time point t0, THC THC0, SIZE S0) and 1 to 2 days before surgery (time point tL, THCL, SL). The relative changes in THC and SIZE of lesions after the first and last NAC cycles were considered as the variables ΔTHC and ΔSIZE. Receiver operating characteristic curve was performed to calculate ΔTHC and ΔSIZE cutoff values to evaluate pathologic response of 93 breast cancers to NAC, which were then prospectively used to predicate response of 61 breast cancers to NAC. RESULTS: The cutoff values of ΔTHC and ΔSIZE for evaluation of breast cancers NAC treatment response were 23.9% and 42.6%. At ΔTHC 23.9%, the predicted treatment response in 61 breast lesions for the time points t1 to t3 was calculated by area under the curve (AUC), which were AUC₁ 0.534 (P = .6668), AUC₂ 0.604 (P = .1893), and AUC₃ 0.674(P =. 0.027), respectively; for ΔSIZE 42.6%, at time points t1 to t3, AUC₁ 0.505 (P = .9121), AUC₂ 0.645 (P = .0115), and AUC₃ 0.719 (P = .0018). CONCLUSION: US-guided DOT ΔTHC 23.9% and US ΔSIZE 42.6% can be used for the response evaluation and earlier prediction of the pathological response after three rounds of chemotherapy.     

Association Between Background Parenchymal Enhancement and Pathologic Complete Remission Throughout the Neoadjuvant Chemotherapy in Breast Cancer Patients

PURPOSE: To retrospectively investigate the quantitative background parenchymal enhancement (BPE) of the contralateral normal breast in patients with unilateral invasive breast cancer throughout multiple monitoring points of neoadjuvant chemotherapy (NAC) and to further determine whether BPE is associated with tumor response, especially at the early stage of NAC. MATERIALS AND METHODS: A total of 90 patients with unilateral breast cancer who then received six or eight cycles of NAC before surgery were analyzed retrospectively. BPE was measured in dynamic contrast-enhanced MRI at baseline and after 2nd, 4th, and 6th NAC, respectively. Correlation between BPE and tumor size was analyzed, and the association between pathologic complete remission (pCR) and BPE was also analyzed. RESULTS: The BPE of contralateral normal breast showed a constant reduction throughout NAC therapy regardless of the menopausal status (P < .001 in all). Both the BPEs and the changes of BPE in each of the three monitoring points were significantly correlated with those in tumor size (P < .05 in all), and the reduction of BPE after 2nd NAC had the largest diagnostic value for pCR (AUC = 0.726, P < .001), particularly in hormonal receptor (HR)-negative patients (OR = 0.243, 95%CI = 0.083 to 0.706, P = .009). CONCLUSION: The BPE of contralateral normal breast had a constant decreased tendency similar to the change of tumor size in NAC. Reduction of BPE at the early stage of NAC was positively associated with pCR, especially in HR-negative status.     

Positive Expression of Programmed Death Ligand 1 in Peritumoral Liver Tissue is Associated with Poor Survival after Curative Resection of Hepatocellular Carcinoma

BACKGROUND: Recurrence or metastasis of hepatocellular carcinoma (HCC) is mainly intrahepatic after curative resection, demonstrating that the peritumoral environment is important but often neglected. Programmed death ligand 1 (PD-L1) in intratumoral liver tissues is a poor prognosis factor whose impact is removed after curative resection. However, PD-L1 expression remains in the peritumoral liver tissues and its distribution and prognostic value are still not clear. METHODS: We assessed the expression of PD-L1 by immunohistochemistry in peritumoral liver tissues from 90 HCC patients who underwent curative hepatectomy. The results were validated in an independent cohort of additional 90 HCC patients. RESULTS: We found PD-L1 positive expression in 31.11% (28/90) of peritumoral tissues. Peritumoral PD-L1 expression was associated with a significantly worse overall survival (OS) (P = .000) and disease-free survival (DFS) (P = .001) compared to the negative expression group. Additionally, peritumoral PD-L1 positivity significantly correlated with vascular invasion and a lower albumin level (≤35 g/L). Univariate and multivariate Cox regression models both revealed peritumoral PD-L1 as an independent prognostic factor for OS (HR = 2.853, P = .002) and DFS (HR = 2.362, P = .003). The prognostic value of PD-L1 positivity was validated in the independent data set. CONCLUSIONS: Our data suggest PD-L1 expression in peritumoral hepatocytes is an independent prognostic factor for OS and DFS. This implies that future anti-cancer therapy should target not only residual tumor cells but also the “soil” for promoting tumor growth. Peritumoral PD-L1 could be a good target for adjuvant therapy after hepatectomy.     

The Assessment of Background Parenchymal Enhancement (BPE) in a High-Risk Population: What Causes BPE?

OBJECTIVE: To investigate promoting factors for background parenchymal enhancement (BPE) in MR mammography (MRM). METHODS: 146 patients were retrospectively evaluated, including 91 high-risk patients (50 BRCA patients, 41 patients with elevated lifetime risk). 56 screening patients were matched to the high-risk cases on the basis of age. The correlation of BPE with factors such as fibroglandular tissue (FGT), age, menopausal status, breast cancer, high-risk precondition as well as motion were investigated using linear regression. RESULTS: BPE positively correlated with FGT (P < .001) and negatively correlated with menopausal status (P < .001). Cancer did not show an effect on BPE (P > .05). A high-risk precondition showed a significant impact on the formation of BPE (P < .05). However, when corrected for motion, the correlation between BPE and a high-risk precondition became weak and insignificant, and a highly significant association between BPE and motion was revealed (P < .01). CONCLUSION: BPE positively correlated with FGT and negatively correlated with age. Cancer did not have an effect on BPE. A high-risk precondition appears to have a negative effect on BPE. However, when corrected for motion, high-risk preconditions became insignificant. Technical as well as physiological influences seem to play an important role in the formation of BPE.     

Common variants of ROCKs and the risk of hypertension,and stroke: Two case-control studies and a follow-up study in Chinese Han population

The Rho kinases (ROCKs) are recognized as a critical regulator of vascular functions in cardiovascular disorders. It is crucial to illustrate the association of ROCKs genetic variation and hypertension and/or stroke events. Herein we aimed at investigating the association of ROCK1 and ROCK2 with hypertension and stroke in Chinese Han population. Seven tagSNPs at ROCK1 and ROCK2 were genotyped in a community-based case-control study consisting of 2012 hypertension cases and 2210 normotensive controls and 4128 subjects were further followed up. In stroke case-control study, 1471 ischemic stroke (IS) inpatients and 607 hemorrhagic stroke (HS) inpatients were collected, and 2443 age-matched controls were selected from the follow-up population. Risks were estimated as odds ratio (OR) and hazard ratio (HR) by logistic and Cox regression. The community-based case-control study didn't identify any significant tagSNPs associated with hypertension even after adjustment for covariates. The follow-up analysis showed that rs1481280 of ROCK1 significantly associated with incident hypertension (HR = 1.130, P = 0.048) after adjusting for covariates. rs7589629 and rs978906 of ROCK2 were significantly associated with incident IS (HR = 1.373, P = 0.004; HR = 1.284, P = 0.026) respectively. In stroke case-control study, rs288980, rs1481280 and rs7237677 were significantly associated with IS and the adjusted ORs (P values) of additive model were 0.879 (0.010), 0.895 (0.036) and 0.857 (0.002) respectively. Furthermore, rs288980, rs7237677 and rs978906 were significantly associated with HS and the adjusted ORs (P values) of additive model were 0.857 (0.025), 0.848 (0.018) and 0.856 (0.027) respectively. Our findings suggest that ROCK1 and ROCK2 contribute to the genetic susceptibility of hypertension and stroke.     

The Functional Roles of the MDM2 Splice Variants P2-MDM2-10 and MDM2-∆5 in Breast Cancer Cells

BACKGROUND: MDM2 is a negative regulator of p53 and is upregulated in numerous human cancers. While different MDM2 splice variants have been observed in both normal tissues and malignant cells, their functions are poorly understood. METHODS: We evaluated the effect of MDM2 splice variants by overexpression in MCF-7 cells and analyses of expression of downstream genes (qPCR and Western blot), subcellular localization (immunofluorescence), cell cycle assays (Nucleocounter3000), apoptosis analysis (Annexin V detection), and induction of senescence (β-galactosidase analysis). RESULTS: In a screen for MDM2 splice variants in MCF-7 breast cancer cells, extended with data from healthy leukocytes, we found P2-MDM2-10 and MDM2-Δ5 to be the splice variants expressed at highest levels. Contrasting MDM2 full-length protein, we found normal tissue expression levels of P2-MDM2-10 and MDM2-Δ5 to be highest in individuals harboring the promoter SNP309TT genotype. While we detected no protein product coded for by MDM2-Δ5, the P2-MDM2-10 variant generated a protein markedly more stable than MDM2-FL. Both splice variants were significantly upregulated in stressed cells (P = 4.3 × 10^?4 and P = 7.1 × 10^?4, respectively). Notably, chemotherapy treatment and overexpression of P2-MDM2-10 or MDM2-Δ5 both lead to increased mRNA levels of the endogenous MDM2-FL (P = .039 and P = .070, respectively) but also the proapoptotic gene PUMA (P = .010 and P = .033, respectively), accompanied by induction of apoptosis and repression of senescence. CONCLUSION: We found P2-MDM2-10 and MDM2-Δ5 to have distinct biological functions in breast cancer cells. GENERAL SIGNIFICANCE: Alternative splicing may influence the oncogenic effects of the MDM2 gene.     

Surveillance,Epidemiology, and End Results-based analysis of the impact of preoperative or postoperative radiotherapy on survival outcomes for T3N0 rectal cancer

Purpose: Preoperative chemoradiation has been established as standard of care for T3/T4 node-positive rectal cancer. Recent work, however, has called into question the overall benefit of radiation for tumors with lower risk characteristics, particularly T3N0 rectal cancers. We retrospectively analyzed T3N0 rectal cancer patients and examined how outcomes differed according to the sequence of treatment received. Methods: The Surveillance, Epidemiology, and End Results (SEER) database was used to analyze T3N0 rectal cancer cases diagnosed between 1998 and 2008. Treatment consisted of surgery alone (No RT), preoperative radiation followed by surgery (Neo-Adjuvant RT), or surgery followed by postoperative radiation (Adjuvant RT). Demographic and tumor characteristics of the three groups were compared using t-tests for the comparison of means. Survival information from the SEER database was utilized to estimate cause-specific survival (CSS) and to generate Kaplan–Meier survival curves. Multivariate analysis (MVA) of features associated with outcomes was conducted using Cox proportional hazards regression models with Adjuvant RT, Neo-Adjuvant RT, No RT, histological grade, tumor size, year of diagnosis, and demographic characteristics as covariates. Results: 10-Year CSS estimates were 66.1% (95% CI 62.3–69.6%; P = 0.02), 73.5% (95% CI 68.9–77.5%; P = 0.02), and 76.1% (95% CI 72.4–79.4%; P = 0.02), for No RT, Neo-Adjuvant RT, and Adjuvant RT, respectively. On MVA, Adjuvant RT (HR = 0.688; 95% CI, 0.578–0.819; P < 0.001) was associated with significantly decreased risk for cancer death. By contrast, Neo-Adjuvant RT was not significantly associated with improved cancer survival (HR = 0.863; 95% CI, 0.715–1.043; P = 0.127). Conclusion: Adjuvant RT was associated with significantly higher CSS when compared with surgery alone, while the benefit of Neo-Adjuvant RT was not significant. This indicates that surgery followed by Adjuvant RT may still be an important treatment plan for T3N0 rectal cancer with potentially significant survival advantages over other treatment sequences.     

Integrated Analysis Identifies Molecular Signatures and Specific Prognostic Factors for Different Gastric Cancer Subtypes

BACKGROUND: Gastric cancer (GC) is the fifth leading cause of cancer-related deaths worldwide. As an effective and easily performed method, microscopy-based Lauren classification has been widely accepted by gastrointestinal surgeons and pathologists for GC subtyping, but molecular characteristics of different Lauren subtypes were poorly revealed. METHODS: GSE62254 was used as a derivation cohort, and GSE15459 was used as a validation cohort. The difference between diffuse and intestinal GC on the gene expression level was measured. Gene ontology (GO) enrichment analysis was performed for both subgroups. Hierarchical clustering and heatmap exhibition were also performed. Kaplan-Meier plot and Cox proportional hazards model were used to evaluate survival grouped by the given genes or hierarchical clusters. RESULTS: A total of 4598 genes were found differentially expressed between diffuse and intestinal GC. Immunity- and cell adhesion–related GOs were enriched for diffuse GC, whereas DNA repair– and cell cycle–related GOs were enriched for intestinal GC. We proposed a 40-gene signature (χ² = 30.71, P < .001) that exhibits better discrimination for prognosis than Lauren classification (χ² = 12.11, P = .002). FRZB [RR (95% CI) = 1.824 (1.115-2.986), P = .017] and EFEMP1 [RR (95% CI) = 1.537 (0.969-2.437), P = .067] were identified as independent prognostic factors only in diffuse GC but not in intestinal GC patients. KRT23 [RR (95% CI) = 1.616 (0.938-2.785), P = .083] was identified as an independent prognostic factor only in intestinal GC patients but not in diffuse GC patients. Similar results were achieved in the validation cohort. CONCLUSION: We found that GCs with different Lauren classifications had different molecular characteristics and identified FRZB, EFEMP1, and KRT23 as subtype-specific prognostic factors for GC patients.     

Analysis of Chemopredictive Assay for Targeting Cancer Stem Cells in Glioblastoma Patients

Introduction: The prognosis of glioblastoma (GBM) treated with standard-of-care maximal surgical resection and concurrent adjuvant temozolomide (TMZ)/radiotherapy remains very poor (less than 15 months). GBMs have been found to contain a small population of cancer stem cells (CSCs) that contribute to tumor propagation, maintenance, and treatment resistance. The highly invasive nature of high-grade gliomas and their inherent resistance to therapy lead to very high rates of recurrence. For these reasons, not all patients with similar diagnoses respond to the same chemotherapy, schedule, or dose. Administration of ineffective anticancer therapy is not only costly but more importantly burdens the patient with unnecessary toxicity and selects for the development of resistant cancer cell clones. We have developed a drug response assay (ChemoID) that identifies the most effective chemotherapy against CSCs and bulk of tumor cells from of a panel of potential treatments, offering great promise for individualized cancer management. Providing the treating physician with drug response information on a panel of approved drugs will aid in personalized therapy selections of the most effective chemotherapy for individual patients, thereby improving outcomes. A prospective study was conducted evaluating the use of the ChemoID drug response assay in GBM patients treated with standard of care. Methods: Forty-one GBM patients (mean age 54 years, 59% male), all eligible for a surgical biopsy, were enrolled in an Institutional Review Board–approved protocol, and fresh tissue samples were collected for drug sensitivity testing. Patients were all treated with standard-of-care TMZ plus radiation with or without maximal surgery, depending on the status of the disease. Patients were prospectively monitored for tumor response, time to recurrence, progression-free survival (PFS), and overall survival (OS). Odds ratio (OR) associations of 12-month recurrence, PFS, and OS outcomes were estimated for CSC, bulk tumor, and combined assay responses for the standard-of-care TMZ treatment; sensitivities/specificities, areas under the curve (AUCs), and risk reclassification components were examined. Results: Median follow-up was 8 months (range 3-49 months). For every 5% increase in in vitro CSC cell kill by TMZ, 12-month patient response (nonrecurrence of cancer) increased two-fold, OR = 2.2 (P = .016). Similar but somewhat less supported associations with the bulk tumor test were seen, OR = 2.75 (P = .07) for each 5% bulk tumor cell kill by TMZ. Combining CSC and bulk tumor assay results in a single model yielded a statistically supported CSC association, OR = 2.36 (P = .036), but a much attenuated remaining bulk tumor association, OR = 1.46 (P = .472). AUCs and [sensitivity/specificity] at optimal outpoints (>40% CSC cell kill and >55% bulk tumor cell kill) were AUC = 0.989 [sensitivity = 100/specificity = 97], 0.972 [100/89], and 0.989 [100/97] for the CSC only, bulk tumor only, and combined models, respectively. Risk categorization of patients was improved by 11% when using the CSC test in conjunction with the bulk test (risk reclassification nonevent net reclassification improvement [NRI] and overall NRI = 0.111, P = .030). Median recurrence time was 20 months for patients with a positive (>40% cell kill) CSC test versus only 3 months for those with a negative CSC test, whereas median recurrence time was 13 months versus 4 months for patients with a positive (>55% cell kill) bulk test versus negative. Similar favorable results for the CSC test were observed for PFS and OS outcomes. Panel results across 14 potential other treatments indicated that 34/41 (83%) potentially more optimal alternative therapies may have been chosen using CSC results, whereas 27/41 (66%) alternative therapies may have been chosen using bulk tumor results. Conclusions: The ChemoID CSC drug response assay has the potential to increase the accuracy of bulk tumor assays to help guide individualized chemotherapy choices. GBM cancer recurrence may occur quickly if the CSC test has a low in vitro cell kill rate even if the bulk tumor test cell kill rate is high.     

Cytoplasmic TrkA Expression as a Screen for Detecting NTRK1 Fusions in Colorectal Cancer

NTRK1 gene fusions, the targets of multikinase inhibitors, are promising therapeutic targets for colorectal cancer (CRC). However, screening methods for detecting NTRK1 gene fusions in CRC tissues have not been reported. In this study, we investigated the potential use of immunohistochemistry (IHC) for detecting NTRK1 gene fusions. We performed and compared IHC with fluorescence in situ hybridization (FISH) in 80 CRC patients. TrkA immunostaining was observed to be both membranous and cytoplasmic and was scored semiquantitatively using staining intensity and proportions. The tumors were observed to be NTRK1 gene fusion-positive when ≥20 out of 100 nuclei in FISH. A significant correlation between the IHC and FISH results for determination of the NTRK1 gene fusions was observed. We measured the cytoplasmic TrkA expression, which showed an area under the receiver operating characteristic (ROC) curve of 0.926 (range: 0.864-0.987, 95% CI, P = .001). By choosing 4.5 (sum of the intensity and proportion scores of cytoplasmic TrkA expression) as the cut-off value for the positive and negative NTRK1 gene fusion groups, the sensitivity and specificity for predicting lymph node metastasis were 100 and 83.8%, respectively (P = .001). Specifically, high cytoplasmic TrkA expression (sum of intensity and proportion scores >4) was associated with the presence of NTRK1 gene fusions (P < .0001, r = 0.528). Taken together, our data showed that IHC for TrkA can be used as an efficient screening method for detecting NTRK1 gene fusions in CRC.     

Contrast-Enhanced CT Density Predicts Response to Sunitinib Therapy in Metastatic Renal Cell Carcinoma Patients

The first-line therapy in metastatic renal cell carcinoma (mRCC), sunitinib, exhibits an objective response rate of approximately 30%. Therapeutic alternatives such as other tyrosine kinase inhibitors, VEGF inhibitors, or mTOR inhibitors emphasize the clinical need to predict the patient's response to sunitinib therapy before treatment initiation. In this study, we evaluated the prognostic value of pretreatment portal venous phase contrast-enhanced computed tomography (CECT) mean tumor density on overall survival (OS), progression-free survival (PFS), and tumor growth in 63 sunitinib-treated mRCC patients. Higher pretreatment CECT tumor density was associated with longer PFS and OS [hazard ratio (HR) = 0.968, P = .002, and HR = 0.956, P = .001, respectively], and CECT density was inversely correlated with tumor growth (P = .010). Receiver operating characteristic analysis identified two CECT density cut-off values (63.67 HU, sensitivity 0.704, specificity 0.694; and 68.67 HU, sensitivity 0.593, specificity 0.806) which yielded subpopulations with significantly different PFS and OS (P < .001). Pretreatment CECT is therefore a promising noninvasive strategy for response prediction in sunitinib-treated mRCC patients, identifying patients who will derive maximum therapeutic benefit.     

NFATc1 Expression as a Prognosticator in Urothelial Carcinoma of the Upper Urinary Tract

We recently found that NFATc1, a member of the NFAT family and a key regulator of the immune response, could induce bladder carcinogenesis and cancer progression. In this study, we immunohistochemically stained for NFATc1 in upper urinary tract urothelial carcinoma (UUTUC) specimens and paired nonneoplastic urothelial tissues. NFATc1 was positive in 51 [52%; 40 (40%) weak (1+), 9 (9%) moderate (2+), and 2 (2%) strong (3+)] of 99 UUTUCs, which was significantly higher than in benign urothelium [30 (36%) of 83; 28 (34%) weak and 2 (2%) moderate] (0 vs 1+/2+/3+, P = .038; 0/1+ vs 2+/3+, P = .023). There were no significant associations between NFATc1 expression pattern and tumor grade or pT stage. However, the positive rates of NFATc1 expression tended to be higher in renal pelvic tumors (60%) than in ureteral tumors (42%; P = .080) as well as in pN+ tumors (75%) than in pN0 tumors (49%; P = .089). Kaplan-Meier and log-rank tests revealed that moderate (2+) to strong (3+) NFATc1 expression correlated with lower progression-free survival (P = .032) and cancer-specific survival (P = .005) rates in the 99 cases. Patients with high (2+/3+) NFATc1 muscle-invasive tumor (n = 9) also had a significantly higher risk of cancer-specific mortality (P = .021) compared to those with low (0/1+) NFATc1 muscle-invasive tumor (n = 53). Thus, compared with nonneoplastic urothelium, a significant increase in the expression of NFATc1 in UUTUC was seen, implying the involvement of NFATc1 signals in the development of UUTUC. The current results further suggest that NFATc1 overexpression serves as a predictor of poor prognosis in patients with UUTUC.     

Proving of a Mathematical Model of Cell Calculation Based on Apparent Diffusion Coefficient

OBJECTIVES: Recently, Atuegwu et al. proposed a mathematical model based on ADC_mean and ADC_min to calculation of cellularity. Our purpose was to compare the calculated cellularity according to the formula with the estimated cell count by histopathology in different tumors. METHODS: For this study, we re-analyzed our previous data regarding associations between ADC parameters and histopathological findings. Overall, 134 patients with different tumors were acquired for the analysis. For all tumors, the number of tumor cells was calculated according to Atuegwu et al. 2013. We performed a correlation analysis between the calculated and estimated cellularity. Thereby, Pearson's correlation coefficient was used and P < .05 was taken to indicate statistical significance in all instances. RESULTS: The estimated and calculated cellularity correlated well together in HNSCC (r = 0.701, P = .016) and lymphomas (r = 0.661, P = .001), and moderately in rectal cancer (r = 0.510, P = .036). There were no statistically significant correlations between the estimated and calculated cellularity in uterine cervical cancer, meningiomas, and in thyroid cancer. CONCLUSION: The proposed formula for cellularity calculation does not apply for all tumors. It may be used for HNSCC, cerebral lymphomas and rectal cancer, but not for uterine cervical cancer, meningioma, and thyroid cancer. Furthermore, its usefulness should be proved for other tumors.     

Luminal (Her2 negative) prognostic index and survival of breast cancer patients

PurposeThe group of luminal (Her2 negative) is distinguished from other subtypes of breast cancer. We aimed to produce a prognostic index specific for luminal (Her2 negative) subtype breast cancer that could assist clinical treatment.MethodsThe test set comprised 406 consecutive luminal (Her2 negative) breast cancer patients. The relationship of 11 clinicopathologic factors including survivin with the 5-year disease-free survival was analyzed.ResultsIn univariate analysis, TNM stage, surgery, tumor size, lymph node involvement, and survivin expression were prognostic factors. In multivariate analysis, tumor size [HR (95% CI): 1.98 (1.12–3.49), p = 0.019], the number of lymph node metastasis [HR (95% CI): 1.75 (1.33–2.29), p < 0.0001] and the expression of progesterone receptor [HR (95% CI): 0.58 (0.36–0.95), p = 0.029] can independently predict prognosis. Prognostic index (PI) was calculated as 0.68 × tumor size + 0.56 × the number of lymph node metastasis − 0.54 × PR. According to the PI, patients were categorized into three groups: low, middle, and high risk group with the 5-year disease-free survival rates of 91.91%, 84.97% and 70.47%, respectively (P < 0.001). In the validation set, the luminal prognostic index (LPI) remained significant.ConclusionThe LPI may be a useful tool for evaluating the outcome of patients with luminal (Her-2 negative) breast cancer.