Induction chemotherapy followed by chemoradiotherapy versus chemoradiotherapy alone as neoadjuvant treatment for locally recurrent rectal cancer: study protocol of a multicentre, open-label, parallel-arms, randomized controlled study (PelvEx II)

Background A resection with clear margins (R0 resection) is the most important prognostic factor in patients with locally recurrent rectal cancer (LRRC). However, this is achieved in only 60 per cent of patients. The aim of this study is to investigate whether the addition of induction chemotherapy to neoadjuvant chemo(re)irradiation improves the R0 resection rate in LRRC. Methods This multicentre, international, open-label, phase III, parallel-arms study will enrol 364 patients with resectable LRRC after previous partial or total mesorectal resection without synchronous distant metastases or recent chemo- and/or radiotherapy treatment. Patients will be randomized to receive either induction chemotherapy (three 3-week cycles of CAPOX (capecitabine, oxaliplatin), four 2-week cycles of FOLFOX (5-fluorouracil, leucovorin, oxaliplatin) or FOLFORI (5-fluorouracil, leucovorin, irinotecan)) followed by neoadjuvant chemoradiotherapy and surgery (experimental arm) or neoadjuvant chemoradiotherapy and surgery alone (control arm). Tumours will be restaged using MRI and, in the experimental arm, a further cycle of CAPOX or two cycles of FOLFOX/FOLFIRI will be administered before chemoradiotherapy in case of stable or responsive disease. The radiotherapy dose will be 25 × 2.0 Gy or 28 × 1.8 Gy in radiotherapy-naive patients, and 15 × 2.0 Gy in previously irradiated patients. The concomitant chemotherapy agent will be capecitabine administered twice daily at a dose of 825 mg/m2 on radiotherapy days. The primary endpoint of the study is the R0 resection rate. Secondary endpoints are long-term oncological outcomes, radiological and pathological response, toxicity, postoperative complications, costs, and quality of life. Discussion This trial protocol describes the PelvEx II study. PelvEx II, designed as a multicentre, open-label, phase III, parallel-arms study, is the first randomized study to compare induction chemotherapy followed by neoadjuvant chemo(re)irradiation and surgery with neoadjuvant chemo(re)irradiation and surgery alone in patients with locally recurrent rectal cancer, with the aim of improving the number of R0 resections

The mitochondrial genome of the phytopathogenic basidiomycete Moniliophthora perniciosa is 109 kb in size and contains a stable integrated plasmid

We present here the sequence of the mitochondrial genome of the basidiomycete phytopathogenic hemibiotrophic fungus Moniliophthora perniciosa, causal agent of the Witches` Broom Disease in Theobroma cacao. The DNA is a circular molecule of 109103 base pairs, with 31.9 % GC, and is the largest sequenced so far. This size is due essentially to the presence of numerous non-conserved hypothetical ORFs. It contains the 14 genes coding for proteins involved in the oxidative phosphorylation, the two rRNA genes, one ORF coding for a ribosomal protein (rps3), and a set of 26 tRNA genes that recognize codons for all amino acids. Seven homing endonucleases are located inside introns. Except atp8, all conserved known genes are in the same orientation. Phylogenetic analysis based on the cox genes agrees with the commonly accepted fungal taxonomy. An uncommon feature of this mitochondrial genome is the presence of a region that contains a set of four, relatively small, nested, inverted repeats enclosing two genes coding for polymerases with an invertron-type structure and three conserved hypothetical genes interpreted as the stable integration of a mitochondrial linear plasmid. The integration of this plasmid seems to be a recent evolutionary event that could have implications in fungal biology. This sequence is available under GenBank accession number AY376688. (c) 2008 The British Mycological Society. Published by Elsevier Ltd. All rights reserved.CNPqCapesCNPq Regional Genoma ProgramSEAGRImFAPESP[02/09280-1

The mitochondrial genome of the phytopathogenic basidiomycete Moniliophthora perniciosa is 109 kb in size and contains a stable integrated plasmid

We present here the sequence of the mitochondrial genome of the basidiomycete phytopathogenic hemibiotrophic fungus Moniliophthora perniciosa, causal agent of the Witches' Broom Disease in Theobroma cacao. The DNA is a circular molecule of 109103 base pairs, with 31.9 % GC, and is the largest sequenced so far. This size is due essentially to the presence of numerous non-conserved hypothetical ORFs. It contains the 14 genes coding for proteins involved in the oxidative phosphorylation, the two rRNA genes, one ORF coding for a ribosomal protein (rps3), and a set of 26 tRNA genes that recognize codons for all amino acids. Seven homing endonucleases are located inside introns. Except atp8, all conserved known genes are in the same orientation. Phylogenetic analysis based on the cox genes agrees with the commonly accepted fungal taxonomy. An uncommon feature of this mitochondrial genome is the presence of a region that contains a set of four, relatively small, nested, inverted repeats enclosing two genes coding for polymerases with an invertron-type structure and three conserved hypothetical genes interpreted as the stable integration of a mitochondrial linear plasmid. The integration of this plasmid seems to be a recent evolutionary event that could have implications in fungal biology. This sequence is available under GenBank accession number AY3766881121011361152CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQCOORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPESFUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESPsem informaçãosem informação02/09280-

The Mitochondrial Genome Of The Phytopathogenic Basidiomycete Moniliophthora Perniciosa Is 109 Kb In Size And Contains A Stable Integrated Plasmid.

We present here the sequence of the mitochondrial genome of the basidiomycete phytopathogenic hemibiotrophic fungus Moniliophthora perniciosa, causal agent of the Witches' Broom Disease in Theobroma cacao. The DNA is a circular molecule of 109,103 base pairs, with 31.9% GC, and is the largest sequenced so far. This size is due essentially to the presence of numerous non-conserved hypothetical ORFs. It contains the 14 genes coding for proteins involved in the oxidative phosphorylation, the two rRNA genes, one ORF coding for a ribosomal protein (rps3), and a set of 26 tRNA genes that recognize codons for all amino acids. Seven homing endonucleases are located inside introns. Except atp8, all conserved known genes are in the same orientation. Phylogenetic analysis based on the cox genes agrees with the commonly accepted fungal taxonomy. An uncommon feature of this mitochondrial genome is the presence of a region that contains a set of four, relatively small, nested, inverted repeats enclosing two genes coding for polymerases with an invertron-type structure and three conserved hypothetical genes interpreted as the stable integration of a mitochondrial linear plasmid. The integration of this plasmid seems to be a recent evolutionary event that could have implications in fungal biology. This sequence is available under GenBank accession number AY376688.1121136-5

Predicting outcomes of pelvic exenteration using machine learning

Aim: We aim to compare machine learning with neural network performance in predicting R0 resection (R0), length of stay > 14 days (LOS), major complication rates at 30 days postoperatively (COMP) and survival greater than 1 year (SURV) for patients having pelvic exenteration for locally advanced and recurrent rectal cancer. Method: A deep learning computer was built and the programming environment was established. The PelvEx Collaborative database was used which contains anonymized data on patients who underwent pelvic exenteration for locally advanced or locally recurrent colorectal cancer between 2004 and 2014. Logistic regression, a support vector machine and an artificial neural network (ANN) were trained. Twenty per cent of the data were used as a test set for calculating prediction accuracy for R0, LOS, COMP and SURV. Model performance was measured by plotting receiver operating characteristic (ROC) curves and calculating the area under the ROC curve (AUROC). Results: Machine learning models and ANNs were trained on 1147 cases. The AUROC for all outcome predictions ranged from 0.608 to 0.793 indicating modest to moderate predictive ability. The models performed best at predicting LOS > 14 days with an AUROC of 0.793 using preoperative and operative data. Visualized logistic regression model weights indicate a varying impact of variables on the outcome in question. Conclusion: This paper highlights the potential for predictive modelling of large international databases. Current data allow moderate predictive ability of both complex ANNs and more classic methods

Predicting outcomes of pelvic exenteration using machine learning

Aim: We aim to compare machine learning with neural network performance in predicting R0 resection (R0), length of stay > 14 days (LOS), major complication rates at 30 days postoperatively (COMP) and survival greater than 1 year (SURV) for patients having pelvic exenteration for locally advanced and recurrent rectal cancer. Method: A deep learning computer was built and the programming environment was established. The PelvEx Collaborative database was used which contains anonymized data on patients who underwent pelvic exenteration for locally advanced or locally recurrent colorectal cancer between 2004 and 2014. Logistic regression, a support vector machine and an artificial neural network (ANN) were trained. Twenty per cent of the data were used as a test set for calculating prediction accuracy for R0, LOS, COMP and SURV. Model performance was measured by plotting receiver operating characteristic (ROC) curves and calculating the area under the ROC curve (AUROC). Results: Machine learning models and ANNs were trained on 1147 cases. The AUROC for all outcome predictions ranged from 0.608 to 0.793 indicating modest to moderate predictive ability. The models performed best at predicting LOS > 14 days with an AUROC of 0.793 using preoperative and operative data. Visualized logistic regression model weights indicate a varying impact of variables on the outcome in question. Conclusion: This paper highlights the potential for predictive modelling of large international databases. Current data allow moderate predictive ability of both complex ANNs and more classic methods

Simultaneous pelvic exenteration and liver resection for primary rectal cancer with synchronous liver metastases: results from the PelvEx Collaborative

At presentation, 15-20% of patients with rectal cancer already have synchronous liver metastases. The aim of this study was to determine the surgical and survival outcomes in patients with advanced rectal cancer who underwent combined pelvic exenteration and liver (oligometastatic) resection