24 research outputs found
New statistical potential for quality assessment of protein models and a survey of energy functions
Abstract Background Scoring functions, such as molecular mechanic forcefields and statistical potentials are fundamentally important tools in protein structure modeling and quality assessment. Results The performances of a number of publicly available scoring functions are compared with a statistical rigor, with an emphasis on knowledge-based potentials. We explored the effect on accuracy of alternative choices for representing interaction center types and other features of scoring functions, such as using information on solvent accessibility, on torsion angles, accounting for secondary structure preferences and side chain orientation. Partially based on the observations made, we present a novel residue based statistical potential, which employs a shuffled reference state definition and takes into account the mutual orientation of residue side chains. Atom- and residue-level statistical potentials and Linux executables to calculate the energy of a given protein proposed in this work can be downloaded from http://www.fiserlab.org/potentials. Conclusions Among the most influential terms we observed a critical role of a proper reference state definition and the benefits of including information about the microenvironment of interaction centers. Molecular mechanical potentials were also tested and found to be over-sensitive to small local imperfections in a structure, requiring unfeasible long energy relaxation before energy scores started to correlate with model quality.</p
Association between Incidental Pelvic Inflammation and Aggressive Prostate Cancer
The impact of pelvic inflammation on prostate cancer (PCa) biology and aggressive phenotype has never been studied. Our study objective was to evaluate the role of pelvic inflammation on PCa aggressiveness and its association with clinical outcomes in patients following radical prostatectomy (RP). This study has been conducted on a retrospective single-institutional consecutive cohort of 2278 patients who underwent robot-assisted laparoscopic prostatectomy (RALP) between 01/2013 and 10/2019. Data from 2085 patients were analyzed to study the association between pelvic inflammation and adverse pathology (AP), defined as Gleason Grade Group (GGG) > 2 and ≥ pT3 stage, at resection. In a subset of 1997 patients, the association between pelvic inflammation and biochemical recurrence (BCR) was studied. Alteration in tumor transcriptome and inflammatory markers in patients with and without pelvic inflammation were studied using microarray analysis, immunohistochemistry, and culture supernatants derived from inflamed sites used in functional assays. Changes in blood inflammatory markers in the study cohort were analyzed by O-link. In univariate analyses, pelvic inflammation emerged as a significant predictor of AP. Multivariate cox proportional-hazards regression analyses showed that high pelvic inflammation with pT3 stage and positive surgical margins significantly affected the time to BCR (p ≤ 0.05). PCa patients with high inflammation had elevated levels of pro-inflammatory cytokines in their tissues and in blood. Genes involved in epithelial-to-mesenchymal transition (EMT) and DNA damage response were upregulated in patients with pelvic inflammation. Attenuation of STAT and IL-6 signaling decreased tumor driving properties of conditioned medium from inflamed sites. Pelvic inflammation exacerbates the progression of prostate cancer and drives an aggressive phenotype.</p
Computational Analysis and Experimental Validation of Gene Predictions in Toxoplasma gondii
Toxoplasma gondii is an obligate intracellular protozoan that infects 20 to 90% of the population. It can cause both acute and chronic infections, many of which are asymptomatic, and, in immunocompromised hosts, can cause fatal infection due to reactivation from an asymptomatic chronic infection. An essential step towards understanding molecular mechanisms controlling transitions between the various life stages and identifying candidate drug targets is to accurately characterize the T. gondii proteome.We have explored the proteome of T. gondii tachyzoites with high throughput proteomics experiments and by comparison to publicly available cDNA sequence data. Mass spectrometry analysis validated 2,477 gene coding regions with 6,438 possible alternative gene predictions; approximately one third of the T. gondii proteome. The proteomics survey identified 609 proteins that are unique to Toxoplasma as compared to any known species including other Apicomplexan. Computational analysis identified 787 cases of possible gene duplication events and located at least 6,089 gene coding regions. Commonly used gene prediction algorithms produce very disparate sets of protein sequences, with pairwise overlaps ranging from 1.4% to 12%. Through this experimental and computational exercise we benchmarked gene prediction methods and observed false negative rates of 31 to 43%.This study not only provides the largest proteomics exploration of the T. gondii proteome, but illustrates how high throughput proteomics experiments can elucidate correct gene structures in genomes
A new molecular signature method for prediction of driver cancer pathways from transcriptional data
In vitro evaluation, biodistribution and scintigraphic imaging in mice of radiolabeled anthrax toxins
Genomic Analysis of Uterine Lavage Fluid Detects Early Endometrial Cancers and Reveals a Prevalent Landscape of Driver Mutations in Women without Histopathologic Evidence of Cancer: A Prospective Cross-Sectional Study.
BACKGROUND:Endometrial cancer is the most common gynecologic malignancy, and its incidence and associated mortality are increasing. Despite the immediate need to detect these cancers at an earlier stage, there is no effective screening methodology or protocol for endometrial cancer. The comprehensive, genomics-based analysis of endometrial cancer by The Cancer Genome Atlas (TCGA) revealed many of the molecular defects that define this cancer. Based on these cancer genome results, and in a prospective study, we hypothesized that the use of ultra-deep, targeted gene sequencing could detect somatic mutations in uterine lavage fluid obtained from women undergoing hysteroscopy as a means of molecular screening and diagnosis. METHODS AND FINDINGS:Uterine lavage and paired blood samples were collected and analyzed from 107 consecutive patients who were undergoing hysteroscopy and curettage for diagnostic evaluation from this single-institution study. The lavage fluid was separated into cellular and acellular fractions by centrifugation. Cellular and cell-free DNA (cfDNA) were isolated from each lavage. Two targeted next-generation sequencing (NGS) gene panels, one composed of 56 genes and the other of 12 genes, were used for ultra-deep sequencing. To rule out potential NGS-based errors, orthogonal mutation validation was performed using digital PCR and Sanger sequencing. Seven patients were diagnosed with endometrial cancer based on classic histopathologic analysis. Six of these patients had stage IA cancer, and one of these cancers was only detectable as a microscopic focus within a polyp. All seven patients were found to have significant cancer-associated gene mutations in both cell pellet and cfDNA fractions. In the four patients in whom adequate tumor sample was available, all tumor mutations above a specific allele fraction were present in the uterine lavage DNA samples. Mutations originally only detected in lavage fluid fractions were later confirmed to be present in tumor but at allele fractions significantly less than 1%. Of the remaining 95 patients diagnosed with benign or non-cancer pathology, 44 had no significant cancer mutations detected. Intriguingly, 51 patients without histopathologic evidence of cancer had relatively high allele fraction (1.0%-30.4%), cancer-associated mutations. Participants with detected driver and potential driver mutations were significantly older (mean age mutated = 57.96, 95% confidence interval [CI]: 3.30-∞, mean age no mutations = 50.35; p-value = 0.002; Benjamini-Hochberg [BH] adjusted p-value = 0.015) and more likely to be post-menopausal (p-value = 0.004; BH-adjusted p-value = 0.015) than those without these mutations. No associations were detected between mutation status and race/ethnicity, body mass index, diabetes, parity, and smoking status. Long-term follow-up was not presently available in this prospective study for those women without histopathologic evidence of cancer. CONCLUSIONS:Using ultra-deep NGS, we identified somatic mutations in DNA extracted both from cell pellets and a never previously reported cfDNA fraction from the uterine lavage. Using our targeted sequencing approach, endometrial driver mutations were identified in all seven women who received a cancer diagnosis based on classic histopathology of tissue curettage obtained at the time of hysteroscopy. In addition, relatively high allele fraction driver mutations were identified in the lavage fluid of approximately half of the women without a cancer diagnosis. Increasing age and post-menopausal status were associated with the presence of these cancer-associated mutations, suggesting the prevalent existence of a premalignant landscape in women without clinical evidence of cancer. Given that a uterine lavage can be easily and quickly performed even outside of the operating room and in a physician's office-based setting, our findings suggest the future possibility of this approach for screening women for the earliest stages of endometrial cancer. However, our findings suggest that further insight into development of cancer or its interruption are needed before translation to the clinic
Genomic Analysis of Uterine Lavage Fluid Detects Early Endometrial Cancers and Reveals a Prevalent Landscape of Driver Mutations in Women without Histopathologic Evidence of Cancer: A Prospective Cross-Sectional Study.
BACKGROUND:Endometrial cancer is the most common gynecologic malignancy, and its incidence and associated mortality are increasing. Despite the immediate need to detect these cancers at an earlier stage, there is no effective screening methodology or protocol for endometrial cancer. The comprehensive, genomics-based analysis of endometrial cancer by The Cancer Genome Atlas (TCGA) revealed many of the molecular defects that define this cancer. Based on these cancer genome results, and in a prospective study, we hypothesized that the use of ultra-deep, targeted gene sequencing could detect somatic mutations in uterine lavage fluid obtained from women undergoing hysteroscopy as a means of molecular screening and diagnosis. METHODS AND FINDINGS:Uterine lavage and paired blood samples were collected and analyzed from 107 consecutive patients who were undergoing hysteroscopy and curettage for diagnostic evaluation from this single-institution study. The lavage fluid was separated into cellular and acellular fractions by centrifugation. Cellular and cell-free DNA (cfDNA) were isolated from each lavage. Two targeted next-generation sequencing (NGS) gene panels, one composed of 56 genes and the other of 12 genes, were used for ultra-deep sequencing. To rule out potential NGS-based errors, orthogonal mutation validation was performed using digital PCR and Sanger sequencing. Seven patients were diagnosed with endometrial cancer based on classic histopathologic analysis. Six of these patients had stage IA cancer, and one of these cancers was only detectable as a microscopic focus within a polyp. All seven patients were found to have significant cancer-associated gene mutations in both cell pellet and cfDNA fractions. In the four patients in whom adequate tumor sample was available, all tumor mutations above a specific allele fraction were present in the uterine lavage DNA samples. Mutations originally only detected in lavage fluid fractions were later confirmed to be present in tumor but at allele fractions significantly less than 1%. Of the remaining 95 patients diagnosed with benign or non-cancer pathology, 44 had no significant cancer mutations detected. Intriguingly, 51 patients without histopathologic evidence of cancer had relatively high allele fraction (1.0%-30.4%), cancer-associated mutations. Participants with detected driver and potential driver mutations were significantly older (mean age mutated = 57.96, 95% confidence interval [CI]: 3.30-∞, mean age no mutations = 50.35; p-value = 0.002; Benjamini-Hochberg [BH] adjusted p-value = 0.015) and more likely to be post-menopausal (p-value = 0.004; BH-adjusted p-value = 0.015) than those without these mutations. No associations were detected between mutation status and race/ethnicity, body mass index, diabetes, parity, and smoking status. Long-term follow-up was not presently available in this prospective study for those women without histopathologic evidence of cancer. CONCLUSIONS:Using ultra-deep NGS, we identified somatic mutations in DNA extracted both from cell pellets and a never previously reported cfDNA fraction from the uterine lavage. Using our targeted sequencing approach, endometrial driver mutations were identified in all seven women who received a cancer diagnosis based on classic histopathology of tissue curettage obtained at the time of hysteroscopy. In addition, relatively high allele fraction driver mutations were identified in the lavage fluid of approximately half of the women without a cancer diagnosis. Increasing age and post-menopausal status were associated with the presence of these cancer-associated mutations, suggesting the prevalent existence of a premalignant landscape in women without clinical evidence of cancer. Given that a uterine lavage can be easily and quickly performed even outside of the operating room and in a physician's office-based setting, our findings suggest the future possibility of this approach for screening women for the earliest stages of endometrial cancer. However, our findings suggest that further insight into development of cancer or its interruption are needed before translation to the clinic
Association between Incidental Pelvic Inflammation and Aggressive Prostate Cancer
The impact of pelvic inflammation on prostate cancer (PCa) biology and aggressive phenotype has never been studied. Our study objective was to evaluate the role of pelvic inflammation on PCa aggressiveness and its association with clinical outcomes in patients following radical prostatectomy (RP). This study has been conducted on a retrospective single-institutional consecutive cohort of 2278 patients who underwent robot-assisted laparoscopic prostatectomy (RALP) between 01/2013 and 10/2019. Data from 2085 patients were analyzed to study the association between pelvic inflammation and adverse pathology (AP), defined as Gleason Grade Group (GGG) > 2 and ≥ pT3 stage, at resection. In a subset of 1997 patients, the association between pelvic inflammation and biochemical recurrence (BCR) was studied. Alteration in tumor transcriptome and inflammatory markers in patients with and without pelvic inflammation were studied using microarray analysis, immunohistochemistry, and culture supernatants derived from inflamed sites used in functional assays. Changes in blood inflammatory markers in the study cohort were analyzed by O-link. In univariate analyses, pelvic inflammation emerged as a significant predictor of AP. Multivariate cox proportional-hazards regression analyses showed that high pelvic inflammation with pT3 stage and positive surgical margins significantly affected the time to BCR (p ≤ 0.05). PCa patients with high inflammation had elevated levels of pro-inflammatory cytokines in their tissues and in blood. Genes involved in epithelial-to-mesenchymal transition (EMT) and DNA damage response were upregulated in patients with pelvic inflammation. Attenuation of STAT and IL-6 signaling decreased tumor driving properties of conditioned medium from inflamed sites. Pelvic inflammation exacerbates the progression of prostate cancer and drives an aggressive phenotype
Summary of mutation allele fractions across patient samples by each mutated gene.
<p>Correlation between the total mutations/gene showed <i>R</i><sup>2</sup> = 0.92 (Pearson correlation coefficient) when compared between cell pellet DNA and cfDNA.</p
Baseline characteristics and pre- and post-hysteroscopy diagnoses of the patient cohort.
<p>Baseline characteristics and pre- and post-hysteroscopy diagnoses of the patient cohort.</p