An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

A search for the decay B+→K+ννˉB^+ \to K^+ \nu \bar{\nu}

We search for the rare flavor-changing neutral-current decay $B^+ \to K^+ \nu \bar{\nu}$ in a data sample of 82 fb$^{-1}$ collected with the {\sl BABAR} detector at the PEP-II B-factory. Signal events are selected by examining the properties of the system recoiling against either a reconstructed hadronic or semileptonic charged-B decay. Using these two independent samples we obtain a combined limit of ${\mathcal B}(B^+ \to K^+ \nu \bar{\nu})<5.2 \times 10^{-5}$ at the 90% confidence level. In addition, by selecting for pions rather than kaons, we obtain a limit of ${\mathcal B}(B^+ \to \pi^+ \nu \bar{\nu})<1.0 \times 10^{-4}$ using only the hadronic B reconstruction method.Comment: 7 pages, 8 postscript figures, submitted to Phys. Rev. Let

High-reflectivity broadband distributed Bragg reflector lattice matched to ZnTe

We report on the realization of a high quality distributed Bragg reflector with both high and low refractive index layers lattice matched to ZnTe. Our structure is grown by molecular beam epitaxy and is based on binary compounds only. The high refractive index layer is made of ZnTe, while the low index material is made of a short period triple superlattice containing MgSe, MgTe, and ZnTe. The high refractive index step of Delta_n=0.5 in the structure results in a broad stopband and the reflectivity coefficient exceeding 99% for only 15 Bragg pairs.Comment: 4 pages, 3 figure

Driver Fusions and Their Implications in the Development and Treatment of Human Cancers.

Gene fusions represent an important class of somatic alterations in cancer. We systematically investigated fusions in 9,624 tumors across 33 cancer types using multiple fusion calling tools. We identified a total of 25,664 fusions, with a 63% validation rate. Integration of gene expression, copy number, and fusion annotation data revealed that fusions involving oncogenes tend to exhibit increased expression, whereas fusions involving tumor suppressors have the opposite effect. For fusions involving kinases, we found 1,275 with an intact kinase domain, the proportion of which varied significantly across cancer types. Our study suggests that fusions drive the development of 16.5% of cancer cases and function as the sole driver in more than 1% of them. Finally, we identified druggable fusions involving genes such as TMPRSS2, RET, FGFR3, ALK, and ESR1 in 6.0% of cases, and we predicted immunogenic peptides, suggesting that fusions may provide leads for targeted drug and immune therapy

EuFe2_2As2_2 under high pressure: an antiferromagnetic bulk superconductor

We report the ac magnetic susceptibility $\chi_{ac}$ and resistivity $\rho$ measurements of EuFe$_2$As$_2$ under high pressure $P$. By observing nearly 100% superconducting shielding and zero resistivity at $P$ = 28 kbar, we establish that $P$-induced superconductivity occurs at $T_c \sim$~30 K in EuFe$_2$As$_2$. $\rho$ shows an anomalous nearly linear temperature dependence from room temperature down to $T_c$ at the same $P$. $\chi_{ac}$ indicates that an antiferromagnetic order of Eu$^{2+}$ moments with $T_N \sim$~20 K persists in the superconducting phase. The temperature dependence of the upper critical field is also determined.Comment: To appear in J. Phys. Soc. Jpn., Vol. 78 No.

Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Types of Cancer

We conducted comprehensive integrative molecular analyses of the complete set of tumors in The Cancer Genome Atlas (TCGA), consisting of approximately 10,000 specimens and representing 33 types of cancer. We performed molecular clustering using data on chromosome-arm-level aneuploidy, DNA hypermethylation, mRNA, and miRNA expression levels and reverse-phase protein arrays, of which all, except for aneuploidy, revealed clustering primarily organized by histology, tissue type, or anatomic origin. The influence of cell type was evident in DNA-methylation-based clustering, even after excluding sites with known preexisting tissue-type-specific methylation. Integrative clustering further emphasized the dominant role of cell-of-origin patterns. Molecular similarities among histologically or anatomically related cancer types provide a basis for focused pan-cancer analyses, such as pan-gastrointestinal, pan-gynecological, pan-kidney, and pan-squamous cancers, and those related by stemness features, which in turn may inform strategies for future therapeutic development. Comprehensive, integrated molecular analysis identifies molecular relationships across a large diverse set of human cancers, suggesting future directions for exploring clinical actionability in cancer treatment

Measurement of the electron energy spectrum and its moments in inclusive B -> Xe nu decays

We report a measurement of the inclusive electron energy spectrum for semileptonic decays of B mesons in a data sample of 52 million Y(4S)-->B(B) over bar decays collected with the BABAR detector at the PEP-II asymmetric-energy B-meson factory at SLAC. We determine the branching fraction, first, second, and third moments of the spectrum for lower cutoffs on the electron energy between 0.6 and 1.5 GeV. We measure the partial branching fraction to be B(B-->Xenu,E-e>0.6 GeV)=[10.36+/-0.06(stat.)+/-0.23(sys.)]%

Improved measurement of CP asymmetries in B-0 ->(c(c)over-bar)K0((*)) decays

We present results on time-dependent CP asymmetries in neutral B decays to several CP eigenstates. The measurements use a data sample of about 227x10(6) Upsilon(4S)-> B (B) over bar decays collected by the BABAR detector at the PEP-II asymmetric-energy B Factory at SLAC. The amplitude of the CPasymmetry, sin2 beta in the standard model, is derived from decay-time distributions from events in which one neutral B meson is fully reconstructed in a final state containing a charmonium meson and the other B meson is determined to be either a B-0 or (0) from its decay products. We measure sin2 beta=0.722 +/- 0.040(stat)+/- 0.023(syst) in agreement with the standard model expectation

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Perspective on Oncogenic Processes at the End of the Beginning of Cancer Genomics

The Cancer Genome Atlas (TCGA) has catalyzed systematic characterization of diverse genomic alterations underlying human cancers. At this historic junction marking the completion of genomic characterization of over 11,000 tumors from 33 cancer types, we present our current understanding of the molecular processes governing oncogenesis. We illustrate our insights into cancer through synthesis of the findings of the TCGA PanCancer Atlas project on three facets of oncogenesis: (1) somatic driver mutations, germline pathogenic variants, and their interactions in the tumor; (2) the influence of the tumor genome and epigenome on transcriptome and proteome; and (3) the relationship between tumor and the microenvironment, including implications for drugs targeting driver events and immunotherapies. These results will anchor future characterization of rare and common tumor types, primary and relapsed tumors, and cancers across ancestry groups and will guide the deployment of clinical genomic sequencing