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

TESS Spots a Compact System of Super-Earths around the Naked-eye Star HR 858

Transiting Exoplanet Survey Satellite (TESS) observations have revealed a compact multiplanet system around the sixth-magnitude star HR 858 (TIC 178155732, TOI 396), located 32 pc away. Three planets, each about twice the size of Earth, transit this slightly evolved, late F-type star, which is also a member of a visual binary. Two of the planets may be in mean motion resonance. We analyze the TESS observations, using novel methods to model and remove instrumental systematic errors, and combine these data with follow-up observations taken from a suite of ground-based telescopes to characterize the planetary system. The HR 858 planets are enticing targets for precise radial velocity observations, secondary eclipse spectroscopy, and measurements of the Rossiter-McLaughlin effect

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

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

TOI-481 b and TOI-892 b: Two Long-period Hot Jupiters from the Transiting Exoplanet Survey Satellite

We present the discovery of two new 10 day period giant planets from the Transiting Exoplanet Survey Satellite mission, whose masses were precisely determined using a wide diversity of ground-based facilities. TOI-481 b and TOI-892 b have similar radii (0.99 0.01 and 1.07 0.02, respectively), and orbital periods (10.3311 days and 10.6266 days, respectively), but significantly different masses (1.53 0.03, respectively). Both planets orbit metal-rich stars ( = dex and = for TOI-481 and TOI-892, respectively) but at different evolutionary stages. TOI-481 is a = 1.14 0.02 = 1.66 0.02 G-type star (=K), that with an age of 6.7 Gyr, is in the turn-off point of the main sequence. TOI-892 on the other hand, is a F-type dwarf star (=K), which has a mass of = 1.28 0.03 and a radius of = 1.39 0.02. TOI-481 b and TOI-892 b join the scarcely populated region of transiting gas giants with orbital periods longer than 10 days, which is important to constrain theories of the formation and structure of hot Jupiters

TOI-431/HIP 26013: a super-Earth and a sub-Neptune transiting a bright, early K dwarf, with a third RV planet

Stars and planetary system

TOI-431/HIP 26013: A super-Earth and a sub-Neptune transiting a bright, early K dwarf, with a third RV planet

We present the bright (Vmag = 9.12), multiplanet system TOI-431, characterized with photometry and radial velocities (RVs). We estimate the stellar rotation period to be 30.5 ± 0.7 d using archival photometry and RVs. Transiting Exoplanet Survey Satellite (TESS) objects of Interest (TOI)-431 b is a super-Earth with a period of 0.49 d, a radius of 1.28 ± 0.04 R, a mass of 3.07 ± 0.35 M, and a density of 8.0 ± 1.0 g cm-3; TOI-431 d is a sub-Neptune with a period of 12.46 d, a radius of 3.29 ± 0.09 R, a mass of 9.90+1.53-1.49 M, and a density of 1.36 ± 0.25 g cm-3. We find a third planet, TOI-431 c, in the High Accuracy Radial velocity Planet Searcher RV data, but it is not seen to transit in the TESS light curves. It has an Msin i of 2.83+0.41-0.34 M, and a period of 4.85 d. TOI-431 d likely has an extended atmosphere and is one of the most well-suited TESS discoveries for atmospheric characterization, while the super-Earth TOI-431 b may be a stripped core. These planets straddle the radius gap, presenting an interesting case-study for atmospheric evolution, and TOI-431 b is a prime TESS discovery for the study of rocky planet phase curves

The Cancer Genome Atlas Comprehensive Molecular Characterization of Renal Cell Carcinoma

Renal cell carcinoma(RCC) is not a single disease, but several histologically defined cancers with different genetic drivers, clinical courses, and therapeutic responses. The current study evaluated 843 RCC from the three major histologic subtypes, including 488 clear cell RCC, 274 papillary RCC, and 81 chromophobe RCC. Comprehensive genomic and phenotypic analysis of the RCC subtypes reveals distinctive features of each subtype that provide the foundation for the development of subtype-specific therapeutic and management strategies for patients affected with these cancers. Somatic alteration of BAP1, PBRM1, and PTEN and altered metabolic pathways correlated with subtype-specific decreased survival, while CDKN2A alteration, increased DNA hypermethylation, and increases in the immune-related Th2 gene expression signature correlated with decreased survival within all major histologic subtypes. CIMP-RCC demonstrated an increased immune signature, and a uniform and distinct metabolic expression pattern identified a subset of metabolically divergent (MD) ChRCC that associated with extremely poor survival

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