At the ends of chromosomes, telomeres are DNA-protein structures that protect the genome from damage, shorten progressively over time in most somatic tissues,¹ and are proposed physiological markers of aging.^2,3 Shorter leukocyte telomeres are correlated with older age, male sex, and other known risk factors for noncommunicable diseases^4-6 and are generally associated with higher risk for cardiovascular diseases,^7,8 type 2 diabetes,⁹ and nonvascular, non-neoplastic causes of mortality.⁸ Whether these associations are causal, however, is unknown. Telomere length has also been implicated in risk of cancer, but the direction and magnitude of the association is uncertain and contradictory across observational studies.^10-14 The uncertainty reflects the considerable difficulty of designing observational studies of telomere length and cancer incidence that are sufficiently robust to reverse causation, confounding, and measurement error.

Although cancer cell secretome profiling is a promising strategy used to identify potential body fluid-accessible cancer biomarkers, questions remain regarding the depth to which the cancer cell secretome can be mined and the efficiency with which researchers can select useful candidates from the growing list of identified proteins. Therefore, we analyzed the secretomes of 23 human cancer cell lines derived from 11 cancer types using one-dimensional SDS-PAGE and nano-LC-MS/MS performed on an LTQ-Orbitrap mass spectrometer to generate a more comprehensive cancer cell secretome. A total of 31,180 proteins was detected, accounting for 4,584 non-redundant proteins, with an average of 1,300 proteins identified per cell line. Using protein secretion-predictive algorithms, 55.8% of the proteins appeared to be released or shed from cells. The identified proteins were selected as potential marker candidates according to three strategies: (i) proteins apparently secreted by one cancer type but not by others (cancer type-specific marker candidates), (ii) proteins released by most cancer cell lines (pan-cancer marker candidates), and (iii) proteins putatively linked to cancer-relevant pathways. We then examined protein expression profiles in the Human Protein Atlas to identify biomarker candidates that were simultaneously detected in the secretomes and highly expressed in cancer tissues. This analysis yielded 6–137 marker candidates selective for each tumor type and 94 potential pan-cancer markers. Among these, we selectively validated monocyte differentiation antigen CD14 (for liver cancer), stromal cell-derived factor 1 (for lung cancer), and cathepsin L1 and interferon-induced 17-kDa protein (for nasopharyngeal carcinoma) as potential serological cancer markers. In summary, the proteins identified from the secretomes of 23 cancer cell lines and the Human Protein Atlas represent a focused reservoir of potential cancer biomarkers.

The OncoDB.HCC (Author Webpage) is based on physical maps of rodent and human genomes containing quantitative trait loci of rodent HCC models and various human HCC somatic aberrations including chromosomal data from loss of heterozygosity and comparative genome hybridization analyses, altered expression of genes from microarray and proteomic studies, and finally experimental data of published HCC genes. Comprehensive integration of HCC genomic aberration data avoids potential pitfalls of data inconsistency from single genomic approach and provides lines of evidence to reveal somatic aberrations from levels of DNA, RNA to protein. Twenty-nine of 30 (96.7%) novel HCC genes with significant altered expressions in compared between tumor and adjacent normal tissues were validated by RT–PCR in 45 pairs of HCC tissues and by matching expression profiles in 57 HCC patients of re-analyzed Stanford HCC microarray data. Comparative mapping of HCC loci in between human aberrant chromosomal regions and QTLs of rodent HCC models revealed 12 syntenic HCC regions with 2 loci effectively narrowed down to 2 Mb. Together, OncoDB.HCC graphically presents comprehensive HCC data integration, reveals important HCC genes and loci for positional cloning and functional studies, and discloses potential molecular targets for improving HCC diagnosis and therapy.

Purpose: Histone deacetylase inhibitors (HDACi) are actively explored as new-generation epigenetic drugs but have low efficacy in cancer monotherapy. To reveal new mechanism for combination therapy, we show that HDACi induce cell death but simultaneously activate tumor-progressive genes to ruin therapeutic efficacy. Combined treatments to target tumorigenesis and HDACi-activated metastasis with low toxic modalities could develop new strategies for long-term cancer therapy. Experimental Design: Because metastasis is the major cause of cancer mortality, we measured cell migration activity and profiled metastasis-related gene expressions in HDACi-treated cancer cells. We developed low toxic combination modalities targeting tumorigenesis and HDACi-activated metastasis for preclinical therapies in mice. Results: We showed that cell migration activity was dramatically and dose dependently enhanced by various classes of HDACi treatments in 13 of 30 examined human breast, gastric, liver, and lung cancer cell lines. Tumor metastasis was also enhanced in HDACi-treated mice. HDACi treatments activated multiple PKCs and downstream substrates along with upregulated proapoptotic p21. For targeting tumorigenesis and metastasis with immediate clinical impact, we showed that new modalities of HDACi combined drugs with PKC inhibitory agent, curcumin or tamoxifen, not only suppressed HDACi-activated tumor progressive proteins and cell migration in vitro but also inhibited tumor growth and metastasis in vivo. Conclusion: Treatments of different structural classes of HDACi simultaneously induced cell death and promoted cell migration and metastasis in multiple cancer cell types. Suppression of HDACi-induced PKCs leads to development of low toxic and long-term therapeutic strategies to potentially treat cancer as a chronic disease. Clin Cancer Res; 18(17); 4691–701. ©2012 AACR.

Background: Genetic loci within the major histocompatibility complex (MHC) have been associated with nasopharyngeal carcinoma (NPC), an Epstein-Barr virus (EBV)-associated cancer, in several GWAS. Results outside this region have varied. Methods: We conducted a meta-analysis of four NPC GWAS among Chinese individuals (2,152 cases; 3,740 controls). Forty-three noteworthy findings outside the MHC region were identified and targeted for replication in a pooled analysis of four independent case–control studies across three regions in Asia (4,716 cases; 5,379 controls). A meta-analysis that combined results from the initial GWA and replication studies was performed. Results: In the combined meta-analysis, rs31489, located within the CLPTM1L/TERT region on chromosome 5p15.33, was strongly associated with NPC (OR = 0.81; P value 6.3 × 10⁻¹³). Our results also provide support for associations reported from published NPC GWAS—rs6774494 (P = 1.5 × 10⁻¹²; located in the MECOM gene region), rs9510787 (P = 5.0 × 10⁻¹⁰; located in the TNFRSF19 gene region), and rs1412829/rs4977756/rs1063192 (P = 2.8 × 10⁻⁸, P = 7.0 × 10⁻⁷, and P = 8.4 × 10⁻⁷, respectively; located in the CDKN2A/B gene region). Conclusions: We have identified a novel association between genetic variation in the CLPTM1L/TERT region and NPC. Supporting our finding, rs31489 and other SNPs in this region have been reported to be associated with multiple cancer sites, candidate-based studies have reported associations between polymorphisms in this region and NPC, the TERT gene has been shown to be important for telomere maintenance and has been reported to be overexpressed in NPC, and an EBV protein expressed in NPC (LMP1) has been reported to modulate TERT expression/telomerase activity. Impact: Our finding suggests that factors involved in telomere length maintenance are involved in NPC pathogenesis. Cancer Epidemiol Biomarkers Prev; 25(1); 188–92. ©2015 AACR.