Two CT features were developed to quantitatively describe lung adenocarcinomas by scoring tumor shape complexity (feature 1: convexity) and intratumor density variation (feature 2: entropy ratio) in ...routinely obtained diagnostic CT scans. The developed quantitative features were analyzed in two independent cohorts (cohort 1: n = 61; cohort 2: n = 47) of patients diagnosed with primary lung adenocarcinoma, retrospectively curated to include imaging and clinical data. Preoperative chest CTs were segmented semi-automatically. Segmented tumor regions were further subdivided into core and boundary sub-regions, to quantify intensity variations across the tumor. Reproducibility of the features was evaluated in an independent test-retest dataset of 32 patients. The proposed metrics showed high degree of reproducibility in a repeated experiment (concordance, CCC≥0.897; dynamic range, DR≥0.92). Association with overall survival was evaluated by Cox proportional hazard regression, Kaplan-Meier survival curves, and the log-rank test. Both features were associated with overall survival (convexity: p = 0.008; entropy ratio: p = 0.04) in Cohort 1 but not in Cohort 2 (convexity: p = 0.7; entropy ratio: p = 0.8). In both cohorts, these features were found to be descriptive and demonstrated the link between imaging characteristics and patient survival in lung adenocarcinoma.
Purpose Prior studies have reported the underuse of deferred treatment (ie active surveillance or watchful waiting) for low risk prostate cancer in the United States. We examined contemporary trends ...in active surveillance and watchful waiting in the nationwide Swedish prostate cancer registry. We also examined factors associated with selection of deferred management, which might provide insight into the rational diffusion of this important management strategy. Materials and Methods We identified 57,713 men with very low risk (T1c, Gleason 6 or less, prostate specific antigen less than 10 ng/ml, prostate specific antigen density less than 0.20 ng/ml/cc, 2 or fewer positive biopsy cores or less than 25% of cores positive), low risk (T1-T2, Gleason 6 or less, and prostate specific antigen less than 10 ng/ml) and intermediate risk prostate cancer (T1-T2, Gleason 7 and/or prostate specific antigen 10 to 20 ng/ml) in the PCBaSe (Prostate Cancer database Sweden) from 1998 to 2011. Subclassification of very low risk disease, and active surveillance vs watchful waiting was possible beginning in 2007. We examined primary treatment selection by risk group and used logistic regression to evaluate factors associated with deferred treatment. Results Overall 13,272 (46%) men with low risk and 8,695 (30%) with intermediate risk prostate cancer chose deferred treatment. Since 2007, 59%, 41% and 16% of very low, low and intermediate risk prostate cancer, respectively, chose active surveillance. Age was by far the strongest determinant of deferred treatment. Education, marital status and comorbidity were significantly but weakly associated with deferring treatment. Conclusions Deferred treatment for low and intermediate risk prostate cancer was frequently used in Sweden. Dissociating diagnosis from treatment in men with a low risk of progression can decrease the rate of overtreatment.
Glioblastoma (GBM) is a highly lethal cancer that is universally refractory to the standard multimodal therapies of surgical resection, radiation, and chemotherapy treatment. Temozolomide (TMZ) is ...currently the best chemotherapy agent for GBM, but the durability of response is epigenetically dependent and often short-lived secondary to tumor resistance. Therapies that can provide synergy to chemoradiation are desperately needed in GBM. There is accumulating evidence that adaptive resistance evolution in GBM is facilitated through treatment-induced epigenetic modifications. Epigenetic alterations of DNA methylation, histone modifications, and chromatin remodeling have all been implicated as mechanisms that enhance accessibility for transcriptional activation of genes that play critical roles in GBM resistance and lethality. Hence, understanding and targeting epigenetic modifications associated with GBM resistance is of utmost priority. In this review, we summarize the latest updates on the impact of epigenetic modifications on adaptive resistance evolution in GBM to therapy.
The production of cytokines in response to DNA-damage events may be an important host defense response to help prevent the escape of pre-cancerous cells. The innate immune pathways involved in these ...events are known to be regulated by cellular molecules such as stimulator of interferon genes (STING), which controls type I interferon and pro-inflammatory cytokine production in response to the presence of microbial DNA or cytosolic DNA that has escaped from the nucleus. STING signaling has been shown to be defective in a variety of cancers, such as colon cancer and melanoma, actions that may enable damaged cells to escape the immunosurveillance system. Here, we report through examination of databases that STING signaling may be commonly suppressed in a greater variety of tumors due to loss-of-function mutation or epigenetic silencing of the STING/cGAS promoter regions. In comparison, RNA activated innate immune pathways controlled by RIG-I/MDA5 were significantly less affected. Examination of reported missense STING variants confirmed that many exhibited a loss-of-function phenotype and could not activate cytokine production following exposure to cytosolic DNA or DNA-damage events. Our data imply that the STING signaling pathway may be recurrently suppressed by a number of mechanisms in a considerable variety of malignant disease and be a requirement for cellular transformation.
Evidence from the management of oligometastases with stereotactic body radiation therapy (SBRT) reveals differences in outcomes based on primary histology. We have previously identified a multigene ...expression index for tumor radiosensitivity (RSI) with validation in multiple independent cohorts. In this study, we assessed RSI in liver metastases and assessed our clinical outcomes after SBRT based on primary histology.
Patients were identified from our prospective, observational protocol. The previously tested RSI 10 gene assay was run on samples and calculated using the published algorithm. An independent cohort of 33 patients with 38 liver metastases treated with SBRT was used for clinical correlation.
A total of 372 unique metastatic liver lesions were identified for inclusion from our prospective, institutional metadata pool. The most common primary histologies for liver metastases were colorectal adenocarcinoma (n=314, 84.4%), breast adenocarcinoma (n=12, 3.2%), and pancreas neuroendocrine (n=11, 3%). There were significant differences in RSI of liver metastases based on histology. The median RSIs for liver metastases in descending order of radioresistance were gastrointestinal stromal tumor (0.57), melanoma (0.53), colorectal neuroendocrine (0.46), pancreas neuroendocrine (0.44), colorectal adenocarcinoma (0.43), breast adenocarcinoma (0.35), lung adenocarcinoma (0.31), pancreas adenocarcinoma (0.27), anal squamous cell cancer (0.22), and small intestine neuroendocrine (0.21) (P<.0001). The 12-month and 24-month Kaplan-Meier rates of local control (LC) for colorectal lesions from the independent clinical cohort were 79% and 59%, compared with 100% for noncolorectal lesions (P=.019), respectively.
In this analysis, we found significant differences based on primary histology. This study suggests that primary histology may be an important factor to consider in SBRT radiation dose selection.
Many gene expression normalization algorithms exist for Affymetrix GeneChip microarrays. The most popular of these is RMA, primarily due to the precision and low noise produced during the process. A ...significant strength of this and similar approaches is the use of the entire set of arrays during both normalization and model-based estimation of signal. However, this leads to differing estimates of expression based on the starting set of arrays, and estimates can change when a single, additional chip is added to the set. Additionally, outlier chips can impact the signals of other arrays, and can themselves be skewed by the majority of the population.
We developed an approach, termed IRON, which uses the best-performing techniques from each of several popular processing methods while retaining the ability to incrementally renormalize data without altering previously normalized expression. This combination of approaches results in a method that performs comparably to existing approaches on artificial benchmark datasets (i.e. spike-in) and demonstrates promising improvements in segregating true signals within biologically complex experiments.
By combining approaches from existing normalization techniques, the IRON method offers several advantages. First, IRON normalization occurs pair-wise, thereby avoiding the need for all chips to be normalized together, which can be important for large data analyses. Secondly, the technique does not require similarity in signal distribution across chips for normalization, which can be important for maintaining biologically relevant differences in a heterogeneous background. Lastly, IRON introduces fewer post-processing artifacts, particularly in data whose behavior violates common assumptions. Thus, the IRON method provides a practical solution to common needs of expression analysis. A software implementation of IRON is available at http://gene.moffitt.org/libaffy/.
A unique 12-chemokine gene expression score (CS) accurately predicted the presence of tumor-localized, ectopic lymph node-like structures (TL-ELNs) and improved overall survival (OS) in primary ...colorectal cancer and metastatic melanoma. We analyzed the correlation between CS, clinicopathological variables, molecular data, and 366 survival in Moffitt Cancer Center's Total Cancer Care (TCC) patients with non-metastatic breast cancer.
Affymetrix gene expression profiles were used to interrogate the CS by the principal component method. Breast tumors were classified as high or low score based on median split, and correlations between clinicopathologic variables, PAM50 molecular subtype, and ELN formation were analyzed using the TCC dataset. Differences in overall survival (OS) and recurrence-free survival (RFS) in the larger KM Plot breast cancer public datasets were compared using Kaplan-Meier curves.
We divided the Total Cancer Care (TCC) breast cancer patients into two groups of high or low CS. Mean CS was 0.24 (range, 2.2-2.1). Patients with higher CS were more likely to be white (172 vs. 159; p = 0.03), had poorly differentiated tumors (112 vs. 59; p <0.0001), ER/PR negative (41 vs. 26) and HER2 positive (36 vs. 19; p = 0.001), and contain TL-ELNs. Higher CS scores were also seen in the basal and HER2+ molecular subtypes. In the KM Plot breast cancer datasets higher CS patients demonstrated superior OS (HR = 0.73, p = 0.008) and RFS (HR 0.76, p = <0.0001), especially in basal and HER2+ patients.
High CS breast tumors tend to be higher grade, basal or HER2+, and present more frequently in Caucasians. However, this group of patients also shows the presence of TL-ELNs within the tumor microenvironment and has better survival outcomes. The CS is a novel tool that can identify breast cancer patients with tumors of a unique intratumoral immune composition and better prognosis. Whether or not the CS is a predictive response marker in breast cancer patients undergoing immunotherapy remains to be determined.
•No technical bias between fresh frozen and FFPE samples.•A high fraction of adenocarcinoma patients with activating KRAS mutations.•Mutations in TP53, STK11 and SMARCA4 linked to poor prognosis in ...adenocarcinoma.•Mutations in CSMD3 linked to better prognosis in squamous cell carcinoma.•Co-mutations in TP53 or STK11 confer poor prognosis in KRAS positive patients.
Non-small cell lung cancer (NSCLC) is a heterogeneous disease with unique combinations of somatic molecular alterations in individual patients, as well as significant differences in populations across the world with regard to mutation spectra and mutation frequencies. Here we aim to describe mutational patterns and linked clinical parameters in a population-based NSCLC cohort.
Using targeted resequencing the mutational status of 82 genes was evaluated in a consecutive Swedish surgical NSCLC cohort, consisting of 352 patient samples from either fresh frozen or formalin fixed paraffin embedded (FFPE) tissues. The panel covers all exons of the 82 genes and utilizes reduced target fragment length and two-strand capture making it compatible with degraded FFPE samples.
We obtained a uniform sequencing coverage and mutation load across the fresh frozen and FFPE samples by adaption of sequencing depth and bioinformatic pipeline, thereby avoiding a technical bias between these two sample types. At large, the mutation frequencies resembled the frequencies seen in other western populations, except for a high frequency of KRAS hotspot mutations (43%) in adenocarcinoma patients. Worse overall survival was observed for adenocarcinoma patients with a mutation in either TP53, STK11 or SMARCA4. In the adenocarcinoma KRAS-mutated group poor survival appeared to be linked to concomitant TP53 or STK11 mutations, and not to KRAS mutation as a single aberration. Similar results were seen in the analysis of publicly available data from the cBioPortal. In squamous cell carcinoma a worse prognosis could be observed for patients with MLL2 mutations, while CSMD3 mutations were linked to a better prognosis.
Here we have evaluated the mutational status of a NSCLC cohort. We could not confirm any survival impact of isolated driver mutations. Instead, concurrent mutations in TP53 and STK11 were shown to confer poor survival in the KRAS-positive adenocarcinoma subgroup.
Dysregulated metabolism is a key driver of maladaptive tumor-reactive T lymphocytes within the tumor microenvironment. Actionable targets that rescue the effector activity of antitumor T cells remain ...elusive. Here, we report that the Sirtuin-2 (Sirt2) NAD+-dependent deacetylase inhibits T cell metabolism and impairs T cell effector functions. Remarkably, upregulation of Sirt2 in human tumor-infiltrating lymphocytes (TILs) negatively correlates with response to TIL therapy in advanced non-small-cell lung cancer. Mechanistically, Sirt2 suppresses T cell metabolism by targeting key enzymes involved in glycolysis, tricarboxylic acid-cycle, fatty acid oxidation, and glutaminolysis. Accordingly, Sirt2-deficient murine T cells exhibit increased glycolysis and oxidative phosphorylation, resulting in enhanced proliferation and effector functions and subsequently exhibiting superior antitumor activity. Importantly, pharmacologic inhibition of Sirt2 endows human TILs with these superior metabolic fitness and effector functions. Our findings unveil Sirt2 as an unexpected actionable target for reprogramming T cell metabolism to augment a broad spectrum of cancer immunotherapies.
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•Sirt2, an NAD+-dependent deacetylase, is overexpressed in TILs•Sirt2 interaction with key metabolic enzymes regulates T cell metabolism•Sirt2-deficient T cells exhibit enhanced glycolysis and oxidative phosphorylation•Sirt2 inhibition enhances effector functions of tumor-reactive T cells
Hamaidi et al. show that Sirt2 activity governs the metabolic fitness of T cells at the tumor bed by blocking the activity of key metabolic enzymes involved in glycolysis, TCA-cycle, FAO, and glutaminolysis, and thus controls the magnitude of antitumor immune responses.
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