Preoperative Evaluation of Patients Undergoing Lung Resection Surgery: Defining the Role of the Anesthesiologist on a Multidisciplinary Team

IN THE FIELD of thoracic surgery, one of the key problems in lung resection is the management and function of the residual lung, which has the potential to interfere with both the pulmonary and cardiovascular systems, and, therefore, influence surgical outcome in terms of morbidity and mortality. Between 2007 and 2013, 5 papers addressing preoperative evaluation and risk stratification were published.1-5 However, the members of the task forces responsible for these documents did not include all the professionals involved in the preoperative surgical evaluation, and the documents mainly addressed the stratification of respiratory risk

Correlation between tumor necrosis factor-alpha and D-dimer levels in non-small cell lung cancer patients

The present study was designed to investigate whether a correlation exists between IL-6, TNF-alpha and coagulation (Thrombin-antithrombin, TATc) or fibrinolysis (D-dimer) activation in non-small cell lung cancer (NSCLC) patients. One hundred thirty patients with NSCLC (n=65, 53 males, mean age 65 +/- 8, adenocarcinoma n=32, squamous cancer n=33) or chronic obstructive pulmonary disease (COPD) (n=65, 51 males, mean age 67 +/- 9) were studied. As control group 65 healthy donors (51 males, mean age 61 +/- 14) were also evaluated. The results obtained showed that median D-dimer levels were higher in NSCLC patients (3.0 microg/ml) compared either to COPD patients (1.1 microg/ml, P<0.05) or controls (0.3 microg/ml, P<0.0001). Positive TNF-alpha levels (>10 pg/ml) were found in 26% of NSCLC compared to 3% of COPD (P<0.002) and 5% of controls (P<0.0005). On the other hand, positive (>8.5 pg/ml) IL-6 levels were found in 53% of NSCLC and 21% of COPD patients, compared to 5% of control subjects (P<0.001). Median TATc levels were elevated in either NSCLC (6.9 microg/l) or COPD (5.7 microg/l) patients compared to controls (1.8 microg/l, P<0.0001). Elevated D-dimer levels were significantly associated to positive TNF-alpha levels in patients without distant metastasis (F=4.3, P<0.05). Moreover, TNF-alpha levels (P<0.01) were independently related to the presence of positive D-dimer levels in patients with non-metastatic NSCLC. These results suggest that increased levels of TNF-alpha might be responsible for an activation of fibrinolysis in patients with NSCLC

Severe rhabdomyolysis associated with pemetrexed-based chemotherapy

Pemetrexed is an antifolate metabolite that inhibits several enzymes involved in the folate pathway. It has activity against various solid tumours, and has been approved for treatment of malignant pleural mesothelioma on the basis of findings from a randomised phase III trial.1 The main toxic effects noted for pemetrexed have been rash, myelosuppression, diarrhoea, mucositis, and reversible elevation of liver enzymes—effects that are preventable partly by vitamin supplementation.

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

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Survival analysis in single N2 station lung adenocarcinoma: The prognostic role of involved lymph nodes and adjuvant therapy

Background: Prognostic factors in patients with single mediastinal station (sN2) involvement continues to be a debated issue. Methods: Data on 213 adenocarcinoma patients with sN2 involvement and who had undergone complete anatomical lung resection and lymphadenectomy, were retrospectively reviewed. Clinical and pathological characteristics together with adjuvant therapy (AD) and node (N) status classifications (number of resected nodes (#RN), number of metastatic nodes (#MN), and node ratio (#MN/#RN = NR) were analyzed. Results: Univariable analysis confirmed that age (0.009), #MN (0.009), NR (0.003), #N1 involved stations (p = 0.003), and skip metastases (p = 0.005) were related to overall survival (OS). Multivariable analysis confirmed, as independent prognostic factors, age &lt;66 years and NR with a three-year OS (3YOS) of 78.7% in NR &lt; 10% vs. 46.6% in NR &gt; 10%. In skip metastases, NR (HR 2.734, 95% CI 1.417–5.277, p = 0.003) and pT stage (HR2.136, 95% CI 1.001–4.557, p = 0.050) were confirmed as independent prognostic factors. AD did not influence the OS of patients with singular positive lymph nodes (p = 0.41), while in patients with multiple lymph nodes and AD, a significantly better 3YOS was demonstrated, i.e., 49.1% vs. 30% (p = 0.004). In patients with N2 + N1 involvement, age (p = 0.002) and AD (p = 0.022) were favorable prognostic factors. Conclusions: Adenocarcinoma patients with single N2 station involvement had a favorable outcome in the case of skip metastases and low NR. Adjuvant therapy improves survival with multiple nodal involvement, while its role in single node involvement should be clarified