Establishment and Validation of Novel Prognostic Subtypes in Hepatocellular Carcinoma Based on Bile Acid Metabolism Gene Signatures Using Bulk and Single-Cell RNA-Seq Data

Hepatocellular carcinoma (HCC) is a highly detrimental cancer type and has limited therapeutic options, posing significant threats to human health. The development of HCC has been associated with a disorder in bile acid (BA) metabolism. In this study, we employed an integrative approach, combining various datasets and omics analyses, to comprehensively characterize the tumor microenvironment in HCC based on genes related to BA metabolism. Our analysis resulted in the classification of HCC samples into four subtypes (C1, C2a, C2b, and C3). Notably, subtype C2a, characterized by the highest bile acid metabolism score (BAMS), exhibited the highest survival probability. This subtype also demonstrated increased immune cell infiltration, lower cell cycle scores, reduced AFP levels, and a lower risk of metastasis compared to subtypes C1 and C3. Subtype C1 displayed poorer survival probability and elevated cell cycle scores. Importantly, the identified subtypes based on BAMS showed potential relevance to the gene expression of drug targets in currently approved drugs and those under clinical research. Genes encoding VEGFR (FLT4 and KDR) and MET were elevated in C2, while genes such as TGFBR1, TGFB1, ADORA3, SRC, BRAF, RET, FLT3, KIT, PDGFRA, and PDGFRB were elevated in C1. Additionally, FGFR2 and FGFR3, along with immune target genes including PDCD1 and CTLA4, were higher in C3. This suggests that subtypes C1, C2, and C3 might represent distinct potential candidates for TGFB1 inhibitors, VEGFR inhibitors, and immune checkpoint blockade treatments, respectively. Significantly, both bulk and single-cell transcriptome analyses unveiled a negative correlation between BA metabolism and cell cycle-related pathways. In vitro experiments further confirmed that the treatment of HCC cell lines with BA receptor agonist ursodeoxycholic acid led to the downregulation of the expression of cell cycle-related genes. Our findings suggest a plausible involvement of BA metabolism in liver carcinogenesis, potentially mediated through the regulation of tumor cell cycles and the immune microenvironment. This preliminary understanding lays the groundwork for future investigations to validate and elucidate the specific mechanisms underlying this potential association. Furthermore, this study provides a novel foundation for future precise molecular typing and the design of systemic clinical trials for HCC therapy.

Tumor subtypes and signature model construction based on chromatin regulators for better prediction of prognosis in uveal melanoma

Background: Uveal Melanoma (UM) is the most prevalent primary intraocular malignancy in adults. This study assessed the importance of chromatin regulators (CRs) in UM and developed a model to predict UM prognosis. Methods: Gene expression data and clinical information for UM were obtained from public databases. Samples were typed according to the gene expression of CRs associated with UM prognosis. The prognostic key genes were further screened by the protein interaction network, and the risk model was to predict UM prognosis using the least absolute shrinkage and selection operator (LASSO) regression analysis and performed a test of the risk mode. In addition, we performed gene set variation analysis, tumor microenvironment, and tumor immune analysis between subtypes and risk groups to explore the mechanisms influencing the development of UM. Results: We constructed a signature model consisting of three CRs (RUVBL1, SIRT3, and SMARCD3), which was shown to be accurate, and valid for predicting prognostic outcomes in UM. Higher immune cell infiltration in poor prognostic subtypes and risk groups. The Tumor immune analysis and Tumor Immune Dysfunction and Exclusion (TIDE) score provided a basis for clinical immunotherapy in UM. Conclusion: The risk model has prognostic value for UM survival and provides new insights into the treatment of UM.

Cell State Transitions and Phenotypic Heterogeneity in Luminal Breast Cancer Implicating MicroRNAs as Potential Regulators

Luminal breast cancer subtypes respond poorly to endocrine and trastuzumab treatments due to cellular heterogeneity arising from the phenotype transitions, accounted for mainly by the loss of receptor expression. The origins of basal-like and human epidermal growth factor receptor 2 (HER2)-overexpressing breast cancer subtypes have been attributed to genetic and protein modifications in stem-like cells and luminal progenitor cell populations, respectively. The post-transcriptional regulation of protein expression is known to be influenced by microRNAs (miRNAs) that are deemed to be master regulators of several biological processes in breast tumorigenesis and progression. Our objective was to identify the fractions of luminal breast cancer cells that share stemness potentials and marker profiles and to elucidate the molecular regulatory mechanism that drives transitions between fractions, leading to receptor discordances. Established breast cancer cell lines of all prominent subtypes were screened for the expression of putative cancer stem cell (CSC) markers and drug transporter proteins using a side population (SP) assay. Flow-cytometry-sorted fractions of luminal cancer cells implanted in immunocompromised mice generated a pre-clinical estrogen receptor alpha (ERα+) animal model with multiple tumorigenic fractions displaying differential expression of drug transporters and hormone receptors. Despite an abundance of estrogen receptor 1 (ESR1) gene transcripts, few fractions transitioned to the triple-negative breast cancer (TNBC) phenotype with a visible loss of ER protein expression and a distinct microRNA expression profile that is reportedly enriched in breast CSCs. The translation of this study has the potential to provide novel therapeutic miRNA-based targets to counter the dreaded subtype transitions and the failure of antihormonal therapies in the luminal breast cancer subtype.

tRNA-Derived RNA Fragments Are Novel Biomarkers for Diagnosis, Prognosis, and Tumor Subtypes in Prostate Cancer

BACKGROUND

tRNA-derived RNA fragments (tRFs) are a novel class of small ncRNA that are derived from precursor or mature tRNAs. Recently, the general relevance of their roles and clinical values in tumorigenesis, metastasis, and recurrence have been increasingly highlighted. However, there has been no specific systematic study to elucidate any potential clinical significance for these tRFs in prostate adenocarcinoma (PRAD), one of the most common and malignant cancers that threatens male health worldwide. Here, we investigate the clinical value of 5'-tRFs in PRAD.

METHODS

Small RNA sequencing data were analyzed to discover new 5'-tRFs biomarkers for PRAD. Machine learning algorithms were used to identify 5'-tRF classifiers to distinguish PRAD tumors from normal tissues. LASSO and Cox regression analyses were used to construct 5'-tRF prognostic predictive models. NMF and consensus clustering analyses were performed on 5'-tRF profiles to identify molecular subtypes of PRAD.

RESULTS

The overall levels of 5'-tRFs were significantly upregulated in the PRAD tumor samples compared to their adjacent normal samples. tRF classifiers composed of 13 5'-tRFs achieved AUC values as high as 0.963, showing high sensitivity and specificity in distinguishing PRAD tumors from normal samples. Multiple 5'-tRFs were identified as being associated with the PRAD prognosis. The tRF score, defined by a set of eight 5'-tRFs, was highly predictive of survival in PRAD patients. The combination of tRF and Gleason scores showed a significantly better performance than the Gleason score alone, suggesting that 5'-tRFs can offer PRAD patients additional and improved prognostic information. Four molecular subtypes of the PRAD tumor were identified based on their 5'-tRF expression profiles. Genetically, these 5'-tRFs PRAD tumor subtypes exhibited distinct genomic landscapes in tumor cells. Clinically, they showed marked differences in survival and clinicopathological features.

CONCLUSIONS

5'-tRFs are potential clinical biomarkers for the diagnosis, prognosis, and classification of tumor subtypes on a molecular level. These can help clinicians formulate personalized treatment plans for PRAD patients and may have similar potential applications for other disease types.

Efficacy of neoadjuvant chemotherapy in male breast cancer compared with female breast cancer

BACKGROUND

Neoadjuvant chemotherapy (NAC) is standard for many females with breast cancer (FBC). The efficacy of NAC in male breast cancer (MaBC) is unclear. The aim of this study was to compare proportions of pathologic complete response (pCR) between MaBC and FBC by tumor subtype (TS).

METHODS

MaBC and FBC treated with NAC between 2010 and 2016, with known TS, were evaluated from the National Cancer Database. Proportions of pCR (ypT0/Tis ypN0) were compared between sexes within TS by Fisher test. Multivariable logistic regression assessed the independent association of sex with pCR. Overall survival (OS) was estimated by Kaplan-Meier.

RESULTS

A total of 385 MaBC and 68,065 FBC were included. Median time from initiation of NAC to surgery was 143 days in MaBC and 148 days in FBC. Proportions of pCR in MaBC and FBC by TS were: hormone receptor-positive/human epidermal growth factor receptor 2-negative (HR+/HER2-): 4.9% vs 9.7%, p = .01; HR+/HER2+: 16.1% vs 33.6%, p < .001; HR-/HER2+: 44.0% vs 53.2%, p = .42; and HR-/HER2-: 21.4% vs 32.1%, p = .18, respectively. FBC had twice the odds of pCR than MaBC (adjusted odds ratio, 2.0; 95% CI, 1.5-2.8; p < .001). Five-year OS for MaBC with pCR vs not was 90% vs 64.7%; p = .02. Five-year OS for FBC with pCR vs not was 91.9% vs 75.3%; p < .01.

CONCLUSIONS

Proportions and odds of pCR to NAC were numerically lower in MaBC compared with FBC for each TS and statistically significant for HR+/HER2- and HR+/HER2+. The independent association of sex with pCR was confirmed in multivariable analysis. pCR is prognostic in both MaBC and FBC.

Breast-conserving therapy is associated with better survival than mastectomy in Early-stage breast cancer: A propensity score analysis

Background

Recent retrospective studies have reported that breast‐conserving therapy (BCT) led to improved overall survival (OS) than mastectomy in some populations. We aimed to compare the efficacy of BCT and mastectomy using the SEER database.

Materials and methods

Between 2010 and 2015, 99,790 eligible patients were identified. We included early‐stage breast cancer patients with 5cm or smaller tumors and three or fewer positive lymph nodes in our study. We compared the OS and breast cancer‐specific survival (BCSS) results among patients with BCT and those with mastectomy. Kaplan‐Meier plots, Cox proportional hazard regressions, competing risk analysis, and multivariate regressions were used to evaluate the outcomes. Propensity‐score matching was used to assemble a cohort of patients with similar baseline characteristics.

Results

In our study, 77,452 (77.6%) patients underwent BCT and 22,338 (22.4%) underwent mastectomy. The 5‐year OS rate was 94.7% in the BCT group and 87.6% in the mastectomy group, and the 5‐year BCSS was 97.2% in the BCT and 94.3% in the mastectomy group. Multivariate analysis in the matched cohort showed that women underwent mastectomy was associated with worse OS (Hazard ratio (HR) = 1.79; 95% confidence intervals (CIs) = 1.59–2.02, p < 0.001) and BCSS (HR = 1.88; 95% CIs = 1.61–2.18, p < 0.001) results compared with those underwent BCT. Patients with different subtypes and age group (>50 years old; ≤50 years old) received BCT showed significantly better OS and BCSS results than those received mastectomy. The effect of surgery choice on survival yielded similar results either for all patients or matched cohorts.

Conclusions

Our study showed that BCT was associated with improved survival compared with mastectomy in early‐stage breast cancer patients. It seems advisable to encourage patients to receive BCT rather than mastectomy in early‐stage patients when feasible and appropriate.

Intratumoral Heterogeneity Promotes Collective Cancer Invasion through NOTCH1 Variation

Cellular and molecular heterogeneity within tumors has long been associated with the progression of cancer to an aggressive phenotype and a poor prognosis. However, how such intratumoral heterogeneity contributes to the invasiveness of cancer is largely unknown. Here, using a tumor bioengineering approach, we investigate the interaction between molecular subtypes within bladder microtumors and the corresponding effects on their invasiveness. Our results reveal heterogeneous microtumors formed by multiple molecular subtypes possess enhanced invasiveness compared to individual cells, even when both cells are not invasive individually. To examine the molecular mechanism of intratumoral heterogeneity mediated invasiveness, live single cell biosensing, RNA interference, and CRISPR-Cas9 gene editing approaches were applied to investigate and control the composition of the microtumors. An agent-based computational model was also developed to evaluate the influence of NOTCH1 variation on DLL4 expression within a microtumor. The data indicate that intratumoral variation in NOTCH1 expression can lead to upregulation of DLL4 expression within the microtumor and enhancement of microtumor invasiveness. Overall, our results reveal a novel mechanism of heterogeneity mediated invasiveness through intratumoral variation of gene expression.

Relationship of established risk factors with breast cancer subtypes

Background

Breast cancer is a heterogeneous disease, divided into subtypes based on the expression of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). Subtypes have different biology and prognosis, with accumulating evidence of different risk factors. The purpose of this study was to compare breast cancer risk factors across tumor subtypes in a large, diverse mammography population.

Methods

Women aged 40–84 without a history of breast cancer with a screening mammogram at three United States health systems from 2006 to 2015 were included. Risk factor questionnaires were completed at mammogram visit, supplemented by electronic health records. Invasive tumor subtype was defined by immunohistochemistry as ER/PR+HER2−, ER/PR+HER2+, ER, and PR−HER2+, or triple‐negative breast cancer (TNBC). Cox proportional hazards models were run for each subtype. Associations of race, reproductive history, prior breast problems, family history, breast density, and body mass index (BMI) were assessed. The association of tumor subtypes with screen detection and interval cancer was assessed using logistic regression among invasive cases.

Results

The study population included 198,278 women with a median of 6.5 years of follow‐up (IQR 4.2–9.0 years). There were 4002 invasive cancers, including 3077 (77%) ER/PR+HER2−, 300 (8%) TNBC, 342 (9%) ER/PR+HER2+, and 126 (3%) ER/PR−HER2+ subtype. In multivariate models, Black women had 2.7 times higher risk of TNBC than white women (HR = 2.67, 95% CI 1.99–3.58). Breast density was associated with increased risk of all subtypes. BMI was more strongly associated with ER/PR+HER2− and HER2+ subtypes among postmenopausal women than premenopausal women. Breast density was more strongly associated with ER/PR+HER2− and TNBC among premenopausal than postmenopausal women. TNBC was more likely to be interval cancer than other subtypes.

Conclusions

These results have implications for risk assessment and understanding of the etiology of breast cancer subtypes. More research is needed to determine what factors explain the higher risk of TNBC for Black women.

Sugar-Sweetened Beverages, Artificially Sweetened Beverages, and Breast Cancer Risk: Results From 2 Prospective US Cohorts

BACKGROUND

Whether consumption of sugar-sweetened beverages (SSBs) or artificially sweetened beverages (ASBs) is associated with the risk of breast cancer is of public health interest.

OBJECTIVES

We sought to evaluate associations between consumption of SSBs and ASBs and risks of total and subtype-specific breast cancer.

METHODS

We followed 82,713 women from the Nurses' Health Study (1980 to 2016) and 93,085 women from the Nurses' Health Study II (1991 to 2017). Cumulatively averaged intakes of SSBs and ASBs from FFQs were tested for associations with incident breast cancer cases and subtypes using Cox regression models. We also evaluated the associations stratified by menopausal status, physical activity, BMI, and alcohol intake.

RESULTS

We documented 11,379 breast cancer cases during 4,655,153 person-years of follow-up. Consumption of SSBs or ASBs was not associated with total breast cancer risk: pooled HRs comparing extreme categories (≥1/day compared with <1/month) were 1.03 (95% CI, 0.95-1.12) and 0.96 (95% CI, 0.91-1.02), respectively. We observed a suggestive interaction by BMI using pooled data (P-interaction = 0.08), where a modestly higher risk of breast cancer with each serving per day increment of SSBs was found in lean women (HR, 1.06; 95% CI, 1.01-1.11) but not among overweight or obese women (HR, 1.00; 95% CI, 0.95-1.06). Moreover, in the pooled, fully adjusted analysis, compared to infrequent consumers (<1/month), those who consumed ≥1 serving of ASBs per day had a lower risk of luminal A breast tumors (HR, 0.90; 95% CI, 0.80-1.01; P-trend = 0.02).

CONCLUSIONS

Although no significant associations were observed overall, consumption of SSBs was associated with a slightly higher risk of breast cancer among lean women. This finding could have occurred by chance and needs confirmation. Our findings also suggest no substantial increase in the risk of breast cancer with consumption of ASBs.

Analysis of Approaches in the Microsurgical Treatment of 102 Cases of Petroclival Meningioma in a Single Center

Objectives: We identified the optimal approaches for treating the diverse tumor subtypes of petroclival meningioma (PM) by analyzing the clinical benefits of various surgical approaches adopted for each subtype. Methods: Tumors in 102 PM patients from a single center who underwent surgical treatment were classified as upper clivus (UC), cavernous sinus (CS), tentorium (TE), or petrous apex (PA) types based on the attachment site of the tumor base and the displacement of the trigeminal nerve. The therapeutic effects of different surgical approaches among the subtypes were evaluated according to the patient outcomes. Results: The subtemporal (33.33%), retrosigmoid (16.67%), and Kawase approaches (50%) were used for the UC type. Simpson I/II resection was achieved in 46.66% of patients with the Kawase approach. Significant differences were found between the other two approaches (P = 0.044) and in the follow-up Karnofsky performance scale (KPS) scores (P = 0.008). The subtemporal (60%) and Kawase approaches (40%) were used for the CS type; neither approach achieved Simpson I/II resection. The retrosigmoid (25.81%) and Kawase approaches (74.19%) were used for the TE type. The Simpson I/II resection rates of the two approaches were 55.55 and 86.95%, respectively, and a significant difference was observed between them (P = 0.039). The retrosigmoid (43.75%) and Kawase approaches (56.25%) were used for the PA type. The Simpson I/II resection rates of the two approaches were 31.25 and 50%, respectively. The resection degrees of the two approaches and the KPS scores at follow-up were significantly different (P = 0.034). Conclusion: The individual microsurgical approaches adopted for the various PM tumor subtypes can provide maximal safe resection and good KPS scores. The Kawase approach is more suitable for PM, especially for UC- and PA-type PM tumors.

Prospective study of a diabetes risk reduction diet and the risk of breast cancer

BACKGROUND

Hyperinsulinemia and higher insulin-like growth factors may increase breast cancer risk. We evaluated a diabetes risk reduction diet (DRRD) and breast cancer risk.

OBJECTIVES

We prospectively evaluated the association between adherence to a DRRD and the incidence of breast cancer.

METHODS

We followed 88,739 women from the Nurses' Health Study (NHS; 1980-2016) and 93,915 women from the NHSII (1991-2017). Incident breast cancer cases (n = 11,943) were confirmed with medical records, and subtypes were determined by tissue microarray data and pathology reports. Information on diet and breast cancer risk factors was repeatedly ascertained in follow-up questionnaires. A DRRD score was derived with 9 factors: lower glycemic index of diet; lower intakes of trans fat, sugar-sweetened beverages/fruit juices, and red/processed meat; higher intakes of cereal fiber, coffee, nuts, and whole fruits; and a higher ratio of polyunsaturated to saturated fat (score range: 9-45). Multivariable-adjusted hazard ratios (MVHRs) and 95% CIs were calculated with Cox proportional hazards models.

RESULTS

Being in the highest compared with the lowest DRRD adherence quintile was associated with a modestly lower breast cancer risk (MVHRQ5vsQ1: 0.89; 95% CI: 0.84, 0.95; P-trend = 0.0002); this was attenuated after adjusting for weight change since age 18 y (MVHRQ5vsQ1: 0.92; 95% CI: 0.87, 0.98; P-trend = 0.01). The inverse association was strongest among women with current BMI < 25 kg/m2 (MVHRQ5vsQ1: 0.89; 95% CI: 0.81, 0.98; P-trend = 0.004; P-interaction = 0.04). Among tumor molecular subtypes, the strongest inverse association was observed with basal-type tumors (MVHRQ5vsQ1: 0.67; 95% CI: 0.45, 1.01; P-trend = 0.04).

CONCLUSIONS

Greater DRRD-adherence was associated with lower breast cancer risk, likely mediated by less weight gain with a DRRD; however, independently of weight change, DRRD-adherence was modestly associated with lower breast cancer risk, particularly among lean women.

Intake of individual fatty acids and risk of prostate cancer in the European prospective investigation into cancer and nutrition

The associations of individual dietary fatty acids with prostate cancer risk have not been examined comprehensively. We examined the prospective association of individual dietary fatty acids with prostate cancer risk overall, by tumor subtypes, and prostate cancer death. 142,239 men from the European Prospective Investigation into Cancer and Nutrition who were free from cancer at recruitment were included. Dietary intakes of individual fatty acids were estimated using center-specific validated dietary questionnaires at baseline and calibrated with 24-h recalls. Multivariable Cox regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). After an average follow-up of 13.9 years, 7,036 prostate cancer cases and 936 prostate cancer deaths were ascertained. Intakes of individual fatty acids were not related to overall prostate cancer risk. There was evidence of heterogeneity in the association of some short chain saturated fatty acids with prostate cancer risk by tumor stage (pheterogeneity < 0.015), with a positive association with risk of advanced stage disease for butyric acid (4:0; HR1SD = 1.08; 95%CI = 1.01-1.15; p-trend = 0.026). There were no associations with fatal prostate cancer, with the exception of a slightly higher risk for those who consumed more eicosenoic acid (22:1n-9c; HR1SD = 1.05; 1.00-1.11; p-trend = 0.048) and eicosapentaenoic acid (20:5n-3c; HR1SD = 1.07; 1.00-1.14; p-trend = 0.045). There was no evidence that dietary intakes of individual fatty acids were associated with overall prostate cancer risk. However, a higher intake of butyric acid might be associated with a higher risk of advanced, whereas intakes of eicosenoic and eicosapentaenoic acids might be positively associated with fatal prostate cancer risk.

Molecular Characterization and Clinical Relevance of Metabolic Expression Subtypes in Human Cancers

Metabolic reprogramming provides critical information for clinical oncology. Using molecular data of 9,125 patient samples from The Cancer Genome Atlas, we identified tumor subtypes in 33 cancer types based on mRNA expression patterns of seven major metabolic processes and assessed their clinical relevance. Our metabolic expression subtypes correlated extensively with clinical outcome: subtypes with upregulated carbohydrate, nucleotide, and vitamin/cofactor metabolism most consistently correlated with worse prognosis, whereas subtypes with upregulated lipid metabolism showed the opposite. Metabolic subtypes correlated with diverse somatic drivers but exhibited effects convergent on cancer hallmark pathways and were modulated by highly recurrent master regulators across cancer types. As a proof-of-concept example, we demonstrated that knockdown of SNAI1 or RUNX1—master regulators of carbohydrate metabolic subtypes—modulates metabolic activity and drug sensitivity. Our study provides a system-level view of metabolic heterogeneity within and across cancer types and identifies pathway cross-talk, suggesting related prognostic, therapeutic, and predictive utility.

Are There Differences in Androgen Receptor Expression in Invasive Breast Cancer in African (Tanzanian) Population in Comparison With the Caucasian (Italian) Population?

PURPOSE

Androgen receptor (AR) has been shown to have prognostic implication on breast cancer (BC). Data on the biological features of African BCs are poor. We decided for the first time to compare AR expression of Tanzanian and Italian BC patients.

PATIENTS AND METHODS

Of the 69 consecutive patients seen at the Bugando Medical Center (Mwanza, Tanzania) from 2003 to 2010, who underwent resection of primary BC evaluable for estrogen receptor, progesterone receptor (PgR), and HER2 only 65 were evaluable for AR by immunohistochemistry. Histopathological assessment and biomolecular determinations were performed at the Cancer Institute of Romagna [Istituto Scientifico Romagnolo per lo studio e la cura dei tumori (IRST)-IRCCS, Meldola, Italy]. Caucasian BC patients were selected from an electronic database and matched (1:2 ratio) for year of diagnosis and age at diagnosis.

RESULTS

The median age of patients at diagnosis was 51 (range 29-83) years for Tanzanian and 53 (range 26-86) years for Italian patients. Tanzanian patients harbored tumors with lower AR expression than Italian patients according to the median percentage of immunopositive tumor cells (30% versus 80%, p < 0.0001) and staining intensity (p = 0.0003). The proportion of AR negative patients was likewise higher among Tanzanian patients as regards both ≥1% and ≥10% cutoffs. AR-positive BCs were higher in luminal A and B tumors and decreased in triple-negative (TN) and HER2-enriched tumors in Tanzanian population.

CONCLUSION

AR loss could represent an unfavorable prognostic marker in the African population. The high frequency of TN tumors with high AR expression could open new perspectives of therapy for population in this low income country.

Fruit and vegetable intake and prostate cancer risk in the European Prospective Investigation into Cancer and Nutrition (EPIC)

Several dietary factors have been studied in relation to prostate cancer; however, most studies have not reported on subtypes of fruit and vegetables or tumor characteristics, and results obtained so far are inconclusive. This study aimed to examine the prospective association of total and subtypes of fruit and vegetable intake with the incidence of prostate cancer overall, by grade and stage of disease, and prostate cancer death. Lifestyle information for 142,239 men participating in the European Prospective Investigation into Cancer and Nutrition from 8 European countries was collected at baseline. Multivariable Cox regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). After an average follow-up time of 13.9 years, 7,036 prostate cancer cases were identified. Compared with the lowest fifth, those in the highest fifth of total fruit intake had a significantly reduced prostate cancer risk (HR = 0.91; 95% CI = 0.83-0.99; p-trend = 0.01). No associations between fruit subtypes and prostate cancer risk were observed, except for citrus fruits, where a significant trend was found (HR = 0.94; 95% CI = 0.86-1.02; p-trend = 0.01). No associations between total and subtypes of vegetables and prostate cancer risk were observed. We found no evidence of heterogeneity in these associations by tumor grade and stage, with the exception of significant heterogeneity by tumor grade (pheterogeneity <0.001) for leafy vegetables. No significant associations with prostate cancer death were observed. The main finding of this prospective study was that a higher fruit intake was associated with a small reduction in prostate cancer risk. Whether this association is causal remains unclear.

Reconstructed Metabolic Network Models Predict Flux-Level Metabolic Reprogramming in Glioblastoma

Developments in genome scale metabolic modeling techniques and omics technologies have enabled the reconstruction of context-specific metabolic models. In this study, glioblastoma multiforme (GBM), one of the most common and aggressive malignant brain tumors, is investigated by mapping GBM gene expression data on the growth-implemented brain specific genome-scale metabolic network, and GBM-specific models are generated. The models are used to calculate metabolic flux distributions in the tumor cells. Metabolic phenotypes predicted by the GBM-specific metabolic models reconstructed in this work reflect the general metabolic reprogramming of GBM, reported both in in-vitro and in-vivo experiments. The computed flux profiles quantitatively predict that major sources of the acetyl-CoA and oxaloacetic acid pool used in TCA cycle are pyruvate dehydrogenase from glycolysis and anaplerotic flux from glutaminolysis, respectively. Also, our results, in accordance with recent studies, predict a contribution of oxidative phosphorylation to ATP pool via a slightly active TCA cycle in addition to the major contributor aerobic glycolysis. We verified our results by using different computational methods that incorporate transcriptome data with genome-scale models and by using different transcriptome datasets. Correct predictions of flux distributions in glycolysis, glutaminolysis, TCA cycle and lipid precursor metabolism validate the reconstructed models for further use in future to simulate more specific metabolic patterns for GBM.

Nonlinear Joint Latent Variable Models and Integrative Tumor Subtype Discovery

Integrative analysis has been used to identify clusters by integrating data of disparate types, such as deoxyribonucleic acid (DNA) copy number alterations and DNA methylation changes for discovering novel subtypes of tumors. Most existing integrative analysis methods are based on joint latent variable models, which are generally divided into two classes: joint factor analysis and joint mixture modeling, with continuous and discrete parameterizations of the latent variables respectively. Despite recent progresses, many issues remain. In particular, existing integration methods based on joint factor analysis may be inadequate to model multiple clusters due to the unimodality of the assumed Gaussian distribution, while those based on joint mixture modeling may not have the ability for dimension reduction and/or feature selection. In this paper, we employ a nonlinear joint latent variable model to allow for flexible modeling that can account for multiple clusters as well as conduct dimension reduction and feature selection. We propose a method, called integrative and regularized generative topographic mapping (irGTM), to perform simultaneous dimension reduction across multiple types of data while achieving feature selection separately for each data type. Simulations are performed to examine the operating characteristics of the methods, in which the proposed method compares favorably against the popular iCluster that is based on a linear joint latent variable model. Finally, a glioblastoma multiforme (GBM) dataset is examined.

Head and neck cancer subtypes with biological and clinical relevance: Meta-analysis of gene-expression data

Head and neck squamous cell carcinoma (HNSCC) is a disease with heterogeneous clinical behavior and response to therapies. Despite the introduction of multimodality treatment, 40–50% of patients with advanced disease recur. Therefore, there is an urgent need to improve the classification beyond the current parameters in clinical use to better stratify patients and the therapeutic approaches. Following a meta-analysis approach we built a large training set to whom we applied a Disease-Specific Genomic Analysis (DSGA) to identify the disease component embedded into the tumor data. Eleven independent microarray datasets were used as validation sets.

Six different HNSCC subtypes that summarize the aberrant alterations occurring during tumor progression were identified. Based on their main biological characteristics and de-regulated signaling pathways, the subtypes were designed as immunoreactive, inflammatory, human papilloma virus (HPV)-like, classical, hypoxia associated, and mesenchymal. Our findings highlighted a more aggressive behavior for mesenchymal and hypoxia-associated subtypes. The Genomics Drug Sensitivity Project was used to identify potential associations with drug sensitivity and significant differences were observed among the six subtypes.

To conclude, we report a robust molecularly defined subtype classification in HNSCC that can improve patient selection and pave the way to the development of appropriate therapeutic strategies.

Integrative and regularized principal component analysis of multiple sources of data

Integration of data of disparate types has become increasingly important to enhancing the power for new discoveries by combining complementary strengths of multiple types of data. One application is to uncover tumor subtypes in human cancer research in which multiple types of genomic data are integrated, including gene expression, DNA copy number, and DNA methylation data. In spite of their successes, existing approaches based on joint latent variable models require stringent distributional assumptions and may suffer from unbalanced scales (or units) of different types of data and non-scalability of the corresponding algorithms. In this paper, we propose an alternative based on integrative and regularized principal component analysis, which is distribution-free, computationally efficient, and robust against unbalanced scales. The new method performs dimension reduction simultaneously on multiple types of data, seeking data-adaptive sparsity and scaling. As a result, in addition to feature selection for each type of data, integrative clustering is achieved. Numerically, the proposed method compares favorably against its competitors in terms of accuracy (in identifying hidden clusters), computational efficiency, and robustness against unbalanced scales. In particular, compared with a popular method, the new method was competitive in identifying tumor subtypes associated with distinct patient survival patterns when applied to a combined analysis of DNA copy number, mRNA expression, and DNA methylation data in a glioblastoma multiforme study. Copyright © 2016 John Wiley & Sons, Ltd.

Identifying Etiologically Distinct Sub-Types of Cancer: A Demonstration Project Involving Breast Cancer

With the advent of increasingly detailed molecular portraits of tumor specimens, much attention has been directed toward identifying clinically distinct subtypes of cancer. Subtyping of tumors can also be accomplished with the goal of identifying distinct etiologies. We demonstrate the use of new methodologies to identify genes that distinguish etiologically heterogeneous subtypes of breast cancer using data from the case-control Cancer and Steroid Hormone Study. Tumor specimens were evaluated using a breast cancer expression panel of 196 genes. Using a statistical measure that distinguishes the degree of etiologic heterogeneity in tumor subtypes, each gene is ranked on the basis of its ability to distinguish etiologically distinct subtypes. This is accomplished independently using case-control comparisons and by examining the concordance odds ratios in double primaries. The estrogen receptor gene, and others in this pathway with expression levels that correlated strongly with estrogen receptor levels, demonstrate high degrees of etiologic heterogeneity in both methods. Our results are consistent with a growing literature that confirms the distinct etiologies of breast cancers classified on the basis of estrogen receptor expression levels. This proof-of-principle project demonstrates the viability of new strategies to identify genomic features that distinguish subtypes of cancer from an etiologic perspective.

Unsupervised outlier profile analysis

In much of the analysis of high-throughput genomic data, “interesting” genes have been selected based on assessment of differential expression between two groups or generalizations thereof. Most of the literature focuses on changes in mean expression or the entire distribution. In this article, we explore the use of C(α) tests, which have been applied in other genomic data settings. Their use for the outlier expression problem, in particular with continuous data, is problematic but nevertheless motivates new statistics that give an unsupervised analog to previously developed outlier profile analysis approaches. Some simulation studies are used to evaluate the proposal. A bivariate extension is described that can accommodate data from two platforms on matched samples. The proposed methods are applied to data from a prostate cancer study.

Heterogeneity of epidemiological factors by breast tumor subtypes in Korean women: a case-case study

Breast cancer is heterogeneous in clinical behavior by subtypes; however, it is unclear how this heterogeneity is related to epidemiological factors. To evaluate the differences in epidemiological factors by breast tumor subtypes, we investigated the associations of epidemiological factors between tumor subtypes in Korean women. From the Seoul Breast Cancer Study, a total of 3,058 patients with breast cancer were included in the analyses. Tumor subtypes were classified based on hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) statuses. The epidemiological factors of each subtype were compared through case-case analyses using multivariate a polytomous logistic regression model adjusted for age and recruiting centers. The distribution of the subtypes was as follows: 1,714 HR+ HER2- (56.0%), 414 HR+ HER2+ (13.5%), 423 HR- HER2+ (13.9%) and 507 HR- HER2- (16.6%) patients with breast cancer. There were significant differences in age, menopausal status, age at menarche, number of children, age at first full-term pregnancy (FFTP), duration of breastfeeding and duration of endogenous estrogen exposure between tumor subtypes (p < 0.05). Compared to HR+ HER2- patients, the other subtype patients showed more frequency in having more numbers of children and less frequency in having earlier menarche, later FFTP and longer endogenous estrogen exposure. Although HR- HER2+ patients were less obese, HR- HER2- patients were younger and more obese. In conclusion, age, body mass index and reproductive factors were differentially associated with breast tumor subtypes suggesting a possible distinct etiology for tumor progression.

State of the science: an update on renal cell carcinoma

Renal cell carcinomas (RCC) are emerging as a complex set of diseases that are having a major socioeconomic impact and showing a continued rise in incidence throughout the world. As the field of urologic oncology faces these trends, several major genomic and mechanistic discoveries are altering our core understanding of this multitude of cancers, including several new rare subtypes of renal cancers. In this review, these new findings are examined and placed in the context of the well-established association of clear cell RCC (ccRCC) with mutations in the von Hippel-Lindau (VHL) gene and resultant aberrant hypoxia inducible factor (HIF) signaling. The impact of novel ccRCC-associated genetic lesions on chromatin remodeling and epigenetic regulation is explored. The effects of VHL mutation on primary ciliary function, extracellular matrix homeostasis, and tumor metabolism are discussed. Studies of VHL proteostasis, with the goal of harnessing the proteostatic machinery to refunctionalize mutant VHL, are reviewed. Translational efforts using molecular tools to elucidate discriminating features of ccRCC tumors and develop improved prognostic and predictive algorithms are presented, and new therapeutics arising from the earliest molecular discoveries in ccRCC are summarized. By creating an integrated review of the key genomic and molecular biological disease characteristics of ccRCC and placing these data in the context of the evolving therapeutic landscape, we intend to facilitate interaction among basic, translational, and clinical researchers involved in the treatment of this devastating disease, and accelerate progress toward its ultimate eradication.

Molecular and epidemiological characteristics of inflammatory breast cancer in Algerian patients

Inflammatory breast cancer (IBC) shows a high incidence in Tunisia and Egypt but epidemiological and molecular characteristics have not been described in Algeria. We compared 117 IBC and 59 non-IBC locally advanced breast cancers (LABC), for estrogen and progesterone receptors, HER2, and EGFR protein expression by immunohistochemistry, and HER2 gene amplification by chromogenic in situ hybridization. Demographic, clinico-pathological, and molecular variables were compared with chi-square and Fisher's exact tests to test for significance (P < 0.05, two-tailed). Overall survival (OS) and disease-free survival (DFS) were plotted using Kaplan-Meier curves and compared using the log-rank test. Tumor emboli were detected in 77% of IBC. Palpable masses were found in all LABC but only in 32% of IBC (P < 0.001). Recurrences were higher in LABC than in IBC (48 vs. 35%; P = 0.14) but OS was worse in IBC (68 vs. 71%; P = 0.06). There were no significant differences between IBC and LABC by demographics or by clinico-pathological parameters. The majority of IBC and LABC tumors were luminal A (62 and 64%), followed by basal (~18%, each), triple negative (~18%, each), and HER2+ (~10%, each) subtypes. In multivariate analyses, grade was associated with worse OS (P = 0.04), and DFS (P < 0.001) in IBC; chemo- and radio-therapy were associated with improved OS and DFS, respectively (P < 0.05 for each) in LABC. In conclusion, IBC in Algeria shows similar characteristics to IBC described for Egypt and Tunisia with subtle molecular differences. Current therapeutic treatments were not very effective in this population and new approaches are much needed.