Ivermectin induces apoptosis of esophageal squamous cell carcinoma via mitochondrial pathway.

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is the most predominant primary malignant tumor among worldwide, especially in China. To date, the successful treatment remains a mainly clinical challenge, it is imperative to develop successful therapeutic agents. METHODS: The anti-proliferative effect of ivermectin on ESCC is investigated in cell model and in nude mice model. Cell apoptosis was assessed using flow cytometry, TUNEL assay and western blotting. Mitochondrial dysfunction was determined by reactive oxygen species accumulation, mitochondrial membrane potential and ATP levels. RESULTS: Our results determined that ivermectin significantly inhibited the proliferation of ESCC cells in vitro and in vivo. Furthermore, we found that ivermectin markedly mediated mitochondrial dysfunction and induced apoptosis of ESCC cells, which indicated the anti-proliferative effect of ivermectin on ESCC cells was implicated in mitochondrial apoptotic pathway. Mechanistically, ivermectin significantly triggered ROS accumulation and inhibited the activation of NF-κB signaling pathway and increased the ratio of Bax/Bcl-2. CONCLUSIONS: These finding indicated that ivermectin has significant anti-tumour potential for ESSC and may be a potential therapeutic candidate against ESCC.

Integration of circulating tumor cell and neutrophil-lymphocyte ratio to identify high-risk metastatic castration-resistant prostate cancer patients.

BACKGROUND: The neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), and circulating tumor cells (CTCs) have been associated with survival in castration-resistant prostate cancer (CRPC). However, no study has examined the prognostic value of NLR and PLR in the context of CTCs. METHODS: Baseline CTCs from mCRPC patients were enumerated using the CellSearch System. Baseline NLR and PLR values were calculated using the data from routine complete blood counts. The associations of CTC, NLR, and PLR values, individually and jointly, with progression-free survival (PFS) and overall survival (OS), were evaluated using Kaplan-Meier analysis, as well as univariate and multivariate Cox models. RESULTS: CTCs were detected in 37 (58.7%) of 63 mCRPC patients, and among them, 16 (25.4%) had ≥5 CTCs. The presence of CTCs was significantly associated with a 4.02-fold increased risk for progression and a 3.72-fold increased risk of death during a median follow-up of 17.6 months. OS was shorter among patients with high levels of NLR or PLR than those with low levels (log-rank P = 0.023 and 0.077). Neither NLR nor PLR was individually associated with PFS. Among the 37 patients with detectable CTCs, those with a high NLR had significantly shorter OS (log-rank P = 0.024); however, among the 26 patients without CTCs, the OS difference between high- and low-NLR groups was not statistically significant. Compared to the patients with CTCs and low NLR, those with CTCs and high levels of NLR had a 3.79-fold risk of death (P = 0.036). This association remained significant after adjusting for covariates (P = 0.031). Combination analyses of CTC and PLR did not yield significant results. CONCLUSION: Among patients with detectable CTCs, the use of NLR could further classify patients into different risk groups, suggesting a complementary role for NLR in CTC-based prognostic stratification in mCRPC.

Prognostic value of HER2 status on circulating tumor cells in advanced-stage breast cancer patients with HER2-negative tumors.

PURPOSE: Discordance between HER2 expression in tumor tissue (tHER2) and HER2 status on circulating tumor cells (cHER2) has been reported. It remains largely underexplored whether patients with tHER2-/cHER2+ can benefit from anti-HER2 targeted therapies. METHODS: cHER2 status was determined in 105 advanced-stage patients with tHER2- breast tumors. Association between cHER2 status and progression-free survival (PFS) was analyzed by univariate and multivariate Cox models and survival differences were compared by Kaplan-Meier method. RESULTS: Compared to the patients with low-risk cHER2 (cHER2+ < 2), those with high-risk cHER2 (cHER2+ ≥ 2) had shorter survival time and an increased risk for disease progression (hazard ratio [HR] 2.16, 95% confidence interval [CI] 1.20-3.88, P = 0.010). Among the patients with high-risk cHER2, those who received anti-HER2 targeted therapies had improved PFS compared with those who did not (HR 0.30, 95% CI 0.10-0.92, P = 0.035). In comparison, anti-HER2 targeted therapy did not affect PFS among those with low-risk cHER2 (HR 0.70, 95% CI 0.36-1.38, P = 0.306). Similar results were obtained after adjusting covariates. A longitudinal analysis of 67 patients with cHER2 detected during follow-ups found that those whose cHER2 status changed from high-risk at baseline to low-risk at first follow-up exhibited a significantly improved survival compared to those whose cHER2 remained high-risk (median PFS: 11.7 weeks vs. 2.0 weeks, log-rank P = 0.001). CONCLUSION: In advanced-stage breast cancer patients with tHER2- tumors, cHER2 status has the potential to guide the use of anti-HER2 targeted therapy in patients with high-risk cHER2.

Multi-regional sequencing reveals intratumor heterogeneity and positive selection of somatic mtDNA mutations in hepatocellular carcinoma and colorectal cancer.

Recent studies have revealed significant intratumor heterogeneity (ITH) of nuclear genome mutations and highlighted its function in tumor progression and treatment resistance. However, the ITH of somatic mitochondrial DNA (mtDNA) mutations detected in cancers remains unknown. In this study, we performed multiregional mtDNA sequencing of tumor and paratumor tissue samples from 12 hepatocellular carcinoma (HCC) and 13 colorectal cancer (CRC) patients. A substantial level of mtDNA mutations was found in paired non-HCC inflammatory tissues, suggesting that these tissues might not be mtDNA-genetically "normal." Moreover, our data indicated that the ITH of somatic mtDNA mutations was a common feature in HCC and CRC patients. In addition, we found that shared mutations which were observed in at least 2 samples in each patient exhibited a significantly higher heteroplasmic level than mutations that were private to a specific tumor region from both HCC (p = 0.039) and CRC patients (p = 0.001). The heteroplasmic level of shared mutations was positively correlated with intratumoral recurrence of mtDNA mutations. We also found that shared mutations in tumor tissues with a higher degree of pathogenicity risk exhibited a higher heteroplasmic level and intratumoral recurrence in both HCC and CRC patients. These findings suggest that some mtDNA mutations may undergo positive selection during the clonal expansion. Taken together, our analyses identified various levels of ITH of somatic mtDNA mutations in HCC and CRC patients and provided evidence supporting the positive selection working on some somatic mtDNA mutations in tumor tissues.

Cancer driver gene discovery through an integrative genomics approach in a non-parametric Bayesian framework.

Motivation: Comprehensive catalogue of genes that drive tumor initiation and progression in cancer is key to advancing diagnostics, therapeutics and treatment. Given the complexity of cancer, the catalogue is far from complete yet. Increasing evidence shows that driver genes exhibit consistent aberration patterns across multiple-omics in tumors. In this study, we aim to leverage complementary information encoded in each of the omics data to identify novel driver genes through an integrative framework. Specifically, we integrated mutations, gene expression, DNA copy numbers, DNA methylation and protein abundance, all available in The Cancer Genome Atlas (TCGA) and developed iDriver, a non-parametric Bayesian framework based on multivariate statistical modeling to identify driver genes in an unsupervised fashion. iDriver captures the inherent clusters of gene aberrations and constructs the background distribution that is used to assess and calibrate the confidence of driver genes identified through multi-dimensional genomic data. Results: We applied the method to 4 cancer types in TCGA and identified candidate driver genes that are highly enriched with known drivers. (e.g.: P < 3.40 × 10 -36 for breast cancer). We are particularly interested in novel genes and observed multiple lines of supporting evidence. Using systematic evaluation from multiple independent aspects, we identified 45 candidate driver genes that were not previously known across these 4 cancer types. The finding has important implications that integrating additional genomic data with multivariate statistics can help identify cancer drivers and guide the next stage of cancer genomics research. Availability and Implementation: The C ++ source code is freely available at https://medschool.vanderbilt.edu/cgg/ . Contacts: hai.yang@vanderbilt.edu or bingshan.li@Vanderbilt.Edu. Supplementary information: Supplementary data are available at Bioinformatics online.

A Routine Laboratory Data-Based Model for Predicting Recurrence After Curative Resection of Stage II Colorectal Cancer.

Background: Use of chemotherapy in stage II colorectal cancer (CRC) is controversial because it improves survival only in some patients. We aimed to develop a statistical model using routine and readily available blood tests to predict the prognosis of patients with stage II CRC and to identify which patients are likely to benefit from chemotherapy. Methods: We divided 422 patients with stage II CRC into a training and a testing set. The association of routine laboratory variables and disease-free survival (DFS) was analyzed. A prognostic model was developed incorporating clinically relevant laboratory variables with demographic and tumor characteristics. A prognostic score was derived by calculating the sum of each variable weighted by its regression coefficient in the model. Model performance was evaluated by constructing receiver operating characteristic curves and calculating the area under the curve (AUC). Results: Significant associations were seen between 5 laboratory variables and patient DFS in univariate analyses. After stepwise selection, 3 variables (carcinoembryonic antigen, hemoglobin, creatinine) were retained in the multivariate model with an AUC of 0.75. Compared with patients with a low prognostic score, those with a medium and high prognostic score had a 1.99- and 4.78-fold increased risk of recurrence, respectively. The results from the training set were validated in the testing set. Moreover, chemotherapy significantly improved DFS in high-risk patients, but not in low- and medium-risk patients. Conclusions: A routine laboratory variable-based model may help predict DFS of patients with stage II CRC and identify high-risk patients more likely to benefit from chemotherapy.

Polymorphisms in genes related to epithelial-mesenchymal transition and risk of non-small cell lung cancer.

The epithelial-mesenchymal transition (EMT) process is a crucial step for tumor invasion and metastasis. Previous research investigating EMT has mostly focused on its role in cancer progression. Recent studies showed that EMT and EMT-driving transcription factor (EMT-TF) expression are early events in lung cancer pathogenesis, implying a potential association between EMT and lung cancer risk. In this study, we examined whether genetic variants in EMT-related genes are associated with risk of non-small cell lung cancer (NSCLC). We used data from a genome-wide association study of 1482 NSCLC cases and 1544 healthy controls as the discovery phase, in which we analyzed 1602 single-nucleotide polymorphisms (SNPs) within 159 EMT-related genes. We then validated the significant SNPs in another 5699 cases and 5815 controls from the National Cancer Institute lung cancer genome-wide association study. Cumulative effects were evaluated for validated SNPs, and a gene-based test was performed to explore gene-level association with disease risk. In the discovery phase, 174 SNPs demonstrated significant associations with NSCLC risk. In the validation phase, seven SNPs mapped to EGFR, NOTCH3, ADGRF1 and SMAD3 were confirmed. Cumulative effect analysis of the significant SNPs demonstrated increasing risk with the number of unfavorable genotypes in the discovery and validation datasets. Gene-based analysis implicated ADGRF1, NOTCH3 and CDH1 as significant for NSCLC risk. Functional prediction revealed several potential mechanisms underlying these associations. Our results suggest that EMT-related gene variants may be involved in susceptibility to NSCLC; if confirmed, they might help identify higher-risk individuals.

Prospective and longitudinal evaluations of telomere length of circulating DNA as a risk predictor of hepatocellular carcinoma in HBV patients.

Prospective and longitudinal epidemiological evidence is needed to assess the association between telomere length and risk of hepatocellular carcinoma (HCC). In 323 cancer-free Korean-American HBV patients with 1-year exclusion window (followed for >1 year and did not develop HCC within 1 year), we measured the relative telomere length (RTL) in baseline serum DNAs and conducted extensive prospective and longitudinal analyses to assess RTL-HCC relationship. We found that long baseline RTL conferred an increased HCC risk compared to short RTL [hazard ratio (HR) = 4.93, P = 0.0005). The association remained prominent when the analysis was restricted to patients with a more stringent 5-year exclusion window (HR = 7.51, P = 0.012), indicating that the association was unlikely due to including undetected HCC patients in the cohort, thus minimizing the reverse-causation limitation in most retrospective studies. Adding baseline RTL to demographic variables increased the discrimination accuracy of the time-dependent receiver operating characteristic analysis from 0.769 to 0.868 (P = 1.0 × 10-5). In a nested longitudinal subcohort of 16 matched cases-control pairs, using a mixed effects model, we observed a trend of increased RTL in cases and decreased RTL in controls along 5 years of follow-up, with a significant interaction of case/control status with time (P for interaction=0.002) and confirmed the association between long RTL and HCC risk [odds ratio [OR] = 3.63, P = 0.016]. In summary, serum DNA RTL may be a novel non-invasive prospective marker of HBV-related HCC. Independent studies are necessary to validate and generalize this finding in diverse populations and assess the clinical applicability of RTL in HCC prediction.

Effects of Cancer Stage and Treatment Differences on Racial Disparities in Survival From Colon Cancer: A United States Population-Based Study.

BACKGROUND & AIMS: We evaluated differences in treatment of black vs white patients with colon cancer and assessed their effects on survival, based on cancer stage. METHODS: We collected data from the Surveillance, Epidemiology, and End Results-Medicare database and identified 6190 black and 61,951 white patients with colon cancer diagnosed from 1998 through 2009 and followed up through 2011. Three sets of 6190 white patients were matched sequentially, using a minimum distance strategy, to the same set of 6190 black patients based on demographic (age; sex; diagnosis year; and Surveillance, Epidemiology, and End Results registry), tumor presentation (demographic plus comorbidities, tumor stage, grade, and size), and treatment (presentation plus therapies) variables. We conducted sensitivity analyses to explore the effects of socioeconomic status in a subcohort that included 2000 randomly selected black patients. Racial differences in treatment were assessed using a logistic regression model; their effects on racial survival disparity were evaluated using the Kaplan-Meier method and the Cox proportional hazards model. RESULTS: After patients were matched for demographic variables, the absolute 5-year difference in survival between black and white patients was 8.3% (white, 59.2% 5-y survival; blacks, 50.9% 5-y survival) (P < .0001); this value decreased significantly, to 5.0% (P < .0001), after patients were matched for tumor presentation, and decreased to 4.9% (P < .0001) when patients were matched for treatment. Differences in treatment therefore accounted for 0.1% of the 8.3% difference in survival between black and white patients. After patients were matched for tumor presentation, racial disparities were observed in almost all types of treatment; the disparities were most prominent for patients with advanced-stage cancer (stages III or IV, up to an 11.1% difference) vs early stage cancer (stages I or II, up to a 4.3% difference). After patients were matched for treatment, there was a greater reduction in disparity for black vs white patients with advanced-stage compared with early-stage cancer. In sensitivity analyses, the 5-year racial survival disparity was 7.7% after demographic match, which was less than the 8.3% observed in the complete cohort. This reduction likely was owing to the differences between the subcohort and the complete cohort in those variables that were not included in the demographic match. This value was reduced to 6.5% (P = .0001) after socioeconomic status was included in the demographic match. The difference decreased significantly to 2.8% (P = .090) after tumor presentation match, but was not reduced further after treatment match. CONCLUSIONS: We observed significant disparities in treatment and survival of black vs white patients with colon cancer. The disparity in survival appears to have been affected more strongly by tumor presentation at diagnosis than treatment. The effects of treatment differences on disparities in survival were greater for patients with advanced-stage vs early-stage cancer.

Prognostic values of cancer associated macrophage-like cells (CAML) enumeration in metastatic breast cancer.

PURPOSE: Circulating cancer associated macrophage-like cells (CAMLs) have been detected in the peripheral blood of patients with solid tumors including breast cancer. However, the prognostic relevance of CAMLs in metastatic breast cancer (MBC) has not been evaluated. In the present study, we aimed to measure CAMLs and circulating tumor cells (CTCs) at baseline and examine their prognostic value in patients with MBC. METHODS: Peripheral blood samples from 127 MBC patients were collected at baseline before starting a new treatment. The detection and enumeration of CAMLs and CTCs in 7.5 ml whole blood were performed using the CellSearch™ system. The associations of CAMLs and CTCs with the progression-free survival (PFS) and overall survival (OS) in the patients were evaluated using Kaplan-Meier curves and Cox proportional hazards modeling. RESULTS: Among 127 MBC patients, 21 (16.5%) were detected with CAMLs and 38 (29.9%) had elevated CTCs (≥5 CTCs/7.5 ml). Patients with CAMLs at baseline had worse PFS and OS with an adjusted hazard ratio (HR) of 1.75 (95% CI 1.03-2.98, P = 0.0374) and 3.75 (95% CI 1.52-9.26, P = 0.0042), compared to patients without CAMLs. Compared with patients with <5 CTCs and without CAMLs, patients with <5 CTCs and with CAMLs, with ≥5 CTCs but without CAMLs, or with ≥5 CTCs and with CAMLs, had an increasing trend of risk of disease progression (HR = 0.84, 3.42 and 4.04 respectively, P for trend <0.0001) and death (HR = 2.66, 6.14, and 9.13, respectively, P for trend <0.0001). CONCLUSION: Baseline enumeration of individual CAMLs is an independent indicator for MBC patients' survival. Evaluation of CAMLs in peripheral blood might provide a potential biomarker with additional prognostic values over CTC enumeration alone in MBC patients.

Longitudinally collected CTCs and CTC-clusters and clinical outcomes of metastatic breast cancer.

PURPOSE: Circulating tumor cell (CTC) is a well-established prognosis predictor for metastatic breast cancer (MBC), and CTC-cluster exhibits significantly higher metastasis-promoting capability than individual CTCs. Because measurement of CTCs and CTC-clusters at a single time point may underestimate their prognostic values, we aimed to analyze longitudinally collected CTCs and CTC-clusters in MBC prognostication. METHODS: CTCs and CTC-clusters were enumerated in 370 longitudinally collected blood samples from 128 MBC patients. The associations between baseline, first follow-up, and longitudinal enumerations of CTCs and CTC-clusters with patient progression-free survival (PFS) and overall survival (OS) were analyzed using Cox proportional hazards models. RESULTS: CTC and CTC-cluster counts at both baseline and first follow-up were significantly associated with patient PFS and OS. Time-dependent analysis of longitudinally collected samples confirmed the significantly unfavorable PFS and OS in patients with ≥5 CTCs, and further demonstrated the independent prognostic values by CTC-clusters compared to CTC-enumeration alone. Longitudinal analyses also identified a link between the size of CTC-clusters and patient OS: compared to the patients without any CTC, those with 2-cell CTC-clusters and ≥3-cell CTC-clusters had a hazard ratio (HR) of 7.96 [95 % confidence level (CI) 2.00-31.61, P = 0.003] and 14.50 (3.98-52.80, P < 0.001), respectively. CONCLUSIONS: In this novel time-dependent analysis of longitudinally collected CTCs and CTC-clusters, we showed that CTC-clusters added additional prognostic values to CTC enumeration alone, and a larger-size CTC-cluster conferred a higher risk of death in MBC patients.

Prospective changes in global DNA methylation and cancer incidence and mortality.

BACKGROUND: Methylation of repetitive elements Alu and LINE-1 in humans is considered a surrogate for global DNA methylation. Previous studies of blood-measured Alu/LINE-1 and cancer risk are inconsistent. METHODS: We studied 1259 prospective methylation measurements from blood drawn 1-4 times from 583 participants from 1999 to 2012. We used Cox regression to evaluate time-dependent methylation as a biomarker for cancer risk and mortality, and linear regression to compare mean differences in methylation over time by cancer status and analyse associations between rate of methylation change and cancer. RESULTS: Time-dependent LINE-1 methylation was associated with prostate cancer incidence (HR: 1.38, 95% CI: 1.01-1.88) and all-cancer mortality (HR: 1.41, 95% CI: 1.03-1.92). The first measurement of Alu methylation (HR: 1.39, 95% CI: 1.08-1.79) was associated with all-cancer mortality. Participants who ultimately developed cancer had lower mean LINE-1 methylation than cancer-free participants 10+ years pre-diagnosis (P<0.01). Rate of Alu methylation change was associated with all-cancer incidence (HR: 3.62, 95% CI: 1.09-12.10). CONCLUSIONS: Our results add longitudinal data on blood Alu and LINE-1 methylation and cancer, and potentially contribute to their use as early-detection biomarkers. Future larger studies are needed and should account for the interval between blood sample collection and cancer diagnosis.

A Phase I/II Study of the Investigational Drug Alisertib in Combination With Abiraterone and Prednisone for Patients With Metastatic Castration-Resistant Prostate Cancer Progressing on Abiraterone.

LESSONS LEARNED: Patients with metastatic castration-resistant prostate cancer did not tolerate the combination of alisertib with abiraterone and prednisone.There was no clear signal indicating that adding alisertib might be beneficial for those patients progressing on abiraterone. BACKGROUND: We hypothesized that Aurora A kinase (AK) contributes to castrate resistance in prostate cancer (PCa) and that inhibiting AK with alisertib can resensitize PCa cells to androgen receptor (AR) inhibitor abiraterone. METHODS: This was a phase I/II trial to determine the safety and efficacy of alisertib when given in combination with abiraterone plus prednisone (AP). Metastatic castration-resistant prostate cancer (mCRPC) patients were treated with dose escalation (alisertib at 30, 40, and 50 mg orally b.i.d., days 1-7 every 21 days) per standard 3+3 design. RESULTS: Nine of 43 planned subjects were enrolled. The maximum tolerated dose (MTD) was not reached, and the dose-limiting toxicities (DLTs) included neutropenic fever (1 of 9), neutropenia (1 of 9), fatigue with memory impairment (1 of 9), and diarrhea/mucositis (1 of 9). No prostate-specific antigen (PSA) decrease or circulating tumor cell (CTC) changes were observed during the study. Pharmacodynamically, adding alisertib did not affect total testosterone or dehydroepiandrosterone (DHEA) levels. There was some change in neuroendocrine markers after therapy. Mean duration on study was 2.5 months. The trial was terminated early. CONCLUSION: A tolerable dose of alisertib in combination with AP in mCRPC was not established in this study. There was no clear signal indicating that alisertib might be beneficial for patients with mCRPC progressing on abiraterone.

Detection and Characterization of Circulating Tumor Associated Cells in Metastatic Breast Cancer.

The availability of blood-based diagnostic testing using a non-invasive technique holds promise for real-time monitoring of disease progression and treatment selection. Circulating tumor cells (CTCs) have been used as a prognostic biomarker for the metastatic breast cancer (MBC). The molecular characterization of CTCs is fundamental to the phenotypic identification of malignant cells and description of the relevant genetic alterations that may change according to disease progression and therapy resistance. However, the molecular characterization of CTCs remains a challenge because of the rarity and heterogeneity of CTCs and technological difficulties in the enrichment, isolation and molecular characterization of CTCs. In this pilot study, we evaluated circulating tumor associated cells in one blood draw by size exclusion technology and cytological analysis. Among 30 prospectively enrolled MBC patients, CTCs, circulating tumor cell clusters (CTC clusters), CTCs of epithelial-mesenchymal transition (EMT) and cancer associated macrophage-like cells (CAMLs) were detected and analyzed. For molecular characterization of CTCs, size-exclusion method for CTC enrichment was tested in combination with DEPArray™ technology, which allows the recovery of single CTCs or pools of CTCs as a pure CTC sample for mutation analysis. Genomic mutations of TP53 and ESR1 were analyzed by targeted sequencing on isolated 7 CTCs from a patient with MBC. The results of genomic analysis showed heterozygous TP53 R248W mutation from one single CTC and pools of three CTCs, and homozygous TP53 R248W mutation from one single CTC and pools of two CTCs. Wild-type ESR1 was detected in the same isolated CTCs. The results of this study reveal that size-exclusion method can be used to enrich and identify circulating tumor associated cells, and enriched CTCs were characterized for genetic alterations in MBC patients, respectively.

Network-based stratification analysis of 13 major cancer types using mutations in panels of cancer genes.

BACKGROUND: Cancers are complex diseases with heterogeneous genetic causes and clinical outcomes. It is critical to classify patients into subtypes and associate the subtypes with clinical outcomes for better prognosis and treatment. Large-scale studies have comprehensively identified somatic mutations across multiple tumor types, providing rich datasets for classifying patients based on genomic mutations. One challenge associated with this task is that mutations are rarely shared across patients. Network-based stratification (NBS) approaches have been proposed to overcome this challenge and used to classify tumors based on exome-level mutations. In routine research and clinical applications, however, usually only a small panel of pre-selected genes is screened for mutations. It is unknown whether such small panels are effective in classifying patients into clinically meaningful subtypes. RESULTS: In this study, we applied NBS to 13 major cancer types with exome-level mutation data and compared the classification based on the full exome data with those focusing only on small sets of genes. Specifically, we investigated three panels, FoundationOne (240 genes), PanCan (127 genes) and TruSeq (48 genes). We showed that small panels not only are effective in clustering tumors but also often outperform full exome data for most cancer types. We further associated subtypes with clinical data and identified 5 tumor types (CRC-Colorectal carcinoma, HNSC-Head and neck squamous cell carcinoma, KIRC-Kidney renal clear cell carcinoma, LUAD-Lung adenocarcinoma and UCEC-Uterine corpus endometrial carcinoma) whose subtypes are significantly associated with overall survival, all based on small panels. CONCLUSION: Our analyses indicate that effective patient subtyping can be carried out using mutations detected in smaller gene panels, probably due to the enrichment of clinically important genes in such panels.

Modeling the overall survival of patients with advanced-stage non-small cell lung cancer using data of routine laboratory tests.

Cancer patients undergo routine clinical monitoring with an array of blood tests that may carry long-term prognostic information. We aimed to develop a new prognostic model predicting survival for patients with advanced non-small cell lung cancer (NSCLC), based on laboratory tests commonly performed in clinical practice. A cohort of 1,161 stage IIIB or IV NSCLC patients was divided into training (n = 773) and testing (n = 388) cohorts. We analyzed the associations of 32 commonly tested laboratory variables with patient survival in the training cohort. We developed a model based on those significant laboratory variables, together with important clinical variables. The model was then evaluated in the testing cohort. Five variables, including albumin, total protein, alkaline phosphatase, blood urea nitrogen and international normalized ratio, were significantly associated with patient survival after stepwise selection. A model incorporating these variables classified patients into low-, medium- and high-risk groups with median survival of 16.9, 7.2 and 2.1 months, respectively (p < 0.0001). Compared with low-risk group, patients in the medium- and high-risk groups had a significantly higher risk of death at 1 year, with hazard ratio (HR) of 1.95 (95% CI 1.62-2.36) and 5.22 (4.30-6.34), respectively. These results were validated in the testing cohort. Overall, we developed a prognostic model relying entirely on readily available variables, with similar predictive power to those which depend on more specialized and expensive molecular assays. Further study is necessary to validate and further refine this model, and compare its performance to models based on more specialized and expensive testing.

CD147 reprograms fatty acid metabolism in hepatocellular carcinoma cells through Akt/mTOR/SREBP1c and P38/PPARα pathways.

BACKGROUND & AIMS: CD147 is a transmembrane glycoprotein which is highly expressed in various human cancers including hepatocellular carcinoma (HCC). A drug Licartin developed with (131)Iodine-labeled antibody against CD147 has been approved by the Chinese Food and Drug Administration (FDA) and enters into clinical use for HCC treatment. Increasing lines of evidence indicate that CD147 is implicated in the metabolism of cancer cells, especially glycolysis. However, the molecular mechanism underlying the relationship between CD147 and aberrant tumor lipid metabolism remains elusive. METHODS: We systematically investigated the role of CD147 in the regulation of lipid metabolism, including de novo lipogenesis and fatty acid ß-oxidation, in HCC cells and explored the underlying molecular mechanisms. RESULTS: Bioinformatic analysis and experimental evidence demonstrated that CD147 significantly contributed to the reprogramming of fatty acid metabolism in HCC cells mainly through two mechanisms. On one hand, CD147 upregulated the expression of sterol regulatory element binding protein 1c (SREBP1c) by activating the Akt/mTOR signaling pathway, which in turn directly activated the transcription of major lipogenic genes FASN and ACC1 to promote de novo lipogenesis. On the other hand, CD147 downregulated peroxisome proliferator-activated receptor alpha (PPARα) and its transcriptional target genes CPT1A and ACOX1 by activating the p38 MAPK signaling pathway to inhibit fatty acid ß-oxidation. Moreover, in vitro and in vivo assays indicated that the CD147-mediated reprogramming of fatty acid metabolism played a critical role in the proliferation and metastasis of HCC cells. CONCLUSION: Our findings demonstrate that CD147 is a critical regulator of fatty acid metabolism, which provides a strong line of evidence for this molecule to be used as a drug target in cancer treatment.

The effects of erythropoiesis-stimulating agents on the short-term and long-term survivals in metastatic breast cancer patients receiving chemotherapy: a SEER population-based study.

Current clinical guidelines state that the use of erythropoiesis-stimulating agents (ESAs) may be considered to treat chemotherapy-induced anemia in the non-curative setting to alleviate anemia-related symptoms. However, no convincing survival benefit has been demonstrated to support the use of ESAs in these patients. Using the comprehensive data collected in the National Cancer Institute (NCI)-surveillance epidemiology and end results (SEER) and Medicare-linked database, we analyzed the effect of ESA use on the short-term (18-month) and long-term (60-month) survival rates of chemotherapy-treated metastatic breast cancer patients. Confounding variables were adjusted using a propensity score approach. We also analyzed the effects of ESA on the survival of patients receiving trastuzumab, a commonly prescribed targeted therapy agent in treating HER2-positive tumors. Metastatic breast cancer patients who received ESA treatment exhibited similar 60-month survival rate to those without ESA treatment (22.8 vs. 24.9%, p = 0.8). ESA-treated patients had a trend toward better 18-month survival [crude hazard ratio (HR) 0.86, 95% confidence intervals (CI) 0.68-1.09, p = 0.21]. This protective effect during the first 18 months of chemotherapy became marginally significant after adjusting for the propensity of receiving ESAs (HR 0.80, 95% CI 0.63-1.01, p = 0.070). An interaction effect between ESA and trastuzumab on patient survival was noticeable but not statistically significant. ESAs did not negatively affect the long-term survival of metastatic breast cancer patients. Moreover, ESAs improved patients' survival during the first 18 months of chemotherapy treatment. These findings endorse the current clinical guideline. Given the short survival of these patients, the potential short-term beneficial effects of ESAs are clinically meaningful.

Prospective assessment of the prognostic value of circulating tumor cells and their clusters in patients with advanced-stage breast cancer.

The enumeration of circulating tumor cells (CTCs) provides important prognostic values in patients with metastatic breast cancer. Recent studies indicate that individual CTCs form clusters and these CTC-clusters play an important role in tumor metastasis. We aimed to assess whether quantification of CTC-clusters provides additional prognostic value over quantification of individual CTCs alone. In 115 prospectively enrolled advanced-stage (III and IV) breast cancer patients, CTCs and CTC-clusters were counted in 7.5 ml whole blood using the CellSearch system at baseline before first-line therapy. The individual and joint effects of CTC and CTC cluster counts on patients' progression-free survival (PFS) were analyzed using Cox proportional hazards modeling. Of the 115 patients, 36 (31.3 %) had elevated baseline CTCs (≥5 CTCs/7.5 ml) and 20 (17.4 %) had CTC-clusters (≥2 CTCs/7.5 ml). Patients with elevated CTCs and CTC-clusters both had worse PFS with a hazard ratio (HR) of 2.76 [95 % confidence interval (CI) 1.57-4.86, P log-rank = 0.0005] and 2.83 (1.48-5.39, P log-rank = 0.001), respectively. In joint analysis, compared with patients with <5 CTCs and without CTC-clusters, patients with elevated CTCs but without clusters, and patients with elevated CTCs and with clusters, had an increasing trend of progression risk, with an HR of 2.21 (1.02-4.78) and 3.32 (1.68-6.55), respectively (P log-rank = 0.0006, P trend = 0.0002). The additional prognostic value of CTC-clusters appeared to be more pronounced in patients with inflammatory breast cancer (IBC), the most aggressive form of breast cancer with the poorest survival. Baseline counts of both individual CTCs and CTC-clusters were associated with PFS in advanced-stage breast cancer patients. CTC-clusters might provide additional prognostic value compared with CTC enumeration alone, in patients with elevated CTCs.

Genetic variations in SLC3A2/CD98 gene as prognosis predictors in non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) is characterized by poor prognosis and only a few molecular markers may be potentially used to predict the risk of progression. This study aims to assess the effects of single nucleotide polymorphisms (SNPs) in the CD98 gene on prognosis of NSCLC patients. We genotyped three potential functional SNPs in CD98 gene using Sequenom iPLEX genotyping system in a cohort of 482 NSCLC patients. Multivariate cox proportional hazards model and Kaplan-Meier curve were used for the survival analysis. The variant-containing genotypes of rs1059292 in 5'-flanking region of CD98 gene were significantly associated with an increased risk of death in the multivariate analysis (Hazard ratio [HR], 1.49; 95% confidence interval [95% CI]: 1.04-2.14 in a dominant model). In stratified analysis, the association remained significant in patients with poor differentiation (HR=1.81, 95% CI=1.01-3.25). In addition, rs1059292 also showed a borderline significant association with T stage (OR=1.49; 95% CI: 0.96-2.35) and N stage (OR=1.53; 95% CI: 0.98-2.39). Functional analysis demonstrated that variant genotype of SNP rs1059292 significantly enhanced the transcription activity of CD98 gene promoter. Our data suggest that genetic variation of rs1059292 in CD98 gene may affect clinical outcome of NSCLC in Chinese population.