Deep learning approaches for the identification of erroneous regions in metagenome-assembled genomes

openMetagenomics has enabled the study of microbial communities at an unprecedented scale. The introduction of metagenomic assembled genomes (MAGs, i.e. genomes for which an isolation procedure has never been carried out) into the field has permitted the study of yet-to-be characterized species, expanding our knowledge of underexplored environments. Still, high sample complexity and species-specific variability increase the chances of chimeric or erroneous assembly reconstructions, jeopardizing the study of highly rich microbiome samples such as those derived from soil. In this thesis work, we leveraged the collection of over 1.5 million microbial genomes that is hosted in the University of Trento to set an algorithm able to identify regions of erroneous junctions between genomic regions that followed from the assembly procedure. First, we built a database of 76 species, from which we extracted 50 genomes each, of nearly perfect completeness and absent contamination. Simulating Illumina short reads at coverage 100X on the so-obtained genomes, we next conducted the assembly procedure on 50 pairs of genomes from the same species for each species, in order to increase the chances of obtaining chimerica assemblies. Putative chimeric assemblies were then assigned to a degree of erroneousness based on a function of the depth of coverage which penalized whichever region does not correspond to the theoretical coverage after re-mapping the simulated reads against each contig: briefly, if a region is not fully mapped by none of the two genomes, is considered erroneously assembled. Next two different deep learning models were fitted on these data in order to predict the presence of misassembled regions in contigs, with the aim of developing a post-assembly quality control tool in order to improve the quality of binning results. All considered models generalize quite well (AUC ~ 0.7/0.8) on chimeric assembly contigs created from the same genomes used to generate the training set contigs, while slightly worse (AUC ~ 0.6/0.7) on contigs that come from genomes not used for training. While to be optimized, the presented model is capable of learning DNA-related properties of the genomic sequences in order to distinguish between correctly and erroneously assembled genomic regions in bacteria.Metagenomics has enabled the study of microbial communities at an unprecedented scale. The introduction of metagenomic assembled genomes (MAGs, i.e. genomes for which an isolation procedure has never been carried out) into the field has permitted the study of yet-to-be characterized species, expanding our knowledge of underexplored environments. Still, high sample complexity and species-specific variability increase the chances of chimeric or erroneous assembly reconstructions, jeopardizing the study of highly rich microbiome samples such as those derived from soil. In this thesis work, we leveraged the collection of over 1.5 million microbial genomes that is hosted in the University of Trento to set an algorithm able to identify regions of erroneous junctions between genomic regions that followed from the assembly procedure. First, we built a database of 76 species, from which we extracted 50 genomes each, of nearly perfect completeness and absent contamination. Simulating Illumina short reads at coverage 100X on the so-obtained genomes, we next conducted the assembly procedure on 50 pairs of genomes from the same species for each species, in order to increase the chances of obtaining chimerica assemblies. Putative chimeric assemblies were then assigned to a degree of erroneousness based on a function of the depth of coverage which penalized whichever region does not correspond to the theoretical coverage after re-mapping the simulated reads against each contig: briefly, if a region is not fully mapped by none of the two genomes, is considered erroneously assembled. Next two different deep learning models were fitted on these data in order to predict the presence of misassembled regions in contigs, with the aim of developing a post-assembly quality control tool in order to improve the quality of binning results. All considered models generalize quite well (AUC ~ 0.7/0.8) on chimeric assembly contigs created from the same genomes used to generate the training set contigs, while slightly worse (AUC ~ 0.6/0.7) on contigs that come from genomes not used for training. While to be optimized, the presented model is capable of learning DNA-related properties of the genomic sequences in order to distinguish between correctly and erroneously assembled genomic regions in bacteria

The paradoxical GH response at OGTT does not predict Pasireotide efficacy but matters for glucose metabolism

Purpose: A paradoxical increase in GH after oral glucose load (GH-Par) characterizes about one-third of acromegaly patients and is associated with a better response to first-generation somatostatin receptor ligands (fg-SRLs). Pasireotide is typically considered as a second-/third-line treatment. Here, we investigated the predictive role of GH-Par in pasireotide response and adverse event development. Methods: we collected a multicenter Italian retrospective cohort of 59 patients treated with pasireotide for at least 3 months, all having GH profile from OGTT. IGF-1 normalization or at least 30% reduction at the last follow-up visit defined a responder patient. Results: Considering the entire cohort, median IGF-1 levels before pasireotide (available in 57 patients) were 1.38 times the upper limit of normal (ULN) in patients with large (median size 18 mm) and invasive (82%) adenomas after failure of fg-SRL treatment. After a 40-month median treatment, pasireotide effectively reduced IGF-1 ULN levels in 41 patients, 37 of whom achieving normalization, and 4 with a ≥ 30% reduction. Thirteen patients were classified as GH-Par. The median pasireotide duration, dosage, and efficacy (9/12 responder in the GH-Par group and 32/45 in the GH-NPar) were similar between groups. However, the occurrence of new-onset or worsening glucose metabolism alterations (GMAs) after pasireotide was more frequent in GH-NPar (from 37 to 80%; p < 0.001) compared to GH-Par patients (from 69 to 76%), likely due to the higher prevalence of pre-existing GMAs in the GH-Par group before starting pasireotide (p = 0.038). Conclusions: The GH-Par does not predict the response to pasireotide in acromegaly but can predict a worse metabolic profile

Rectal Sparing Approach after preoperative Radio- and/or Chemo-therapy (ReSARCh): a prospective, multicenter, observational study

BACKGROUND: Rectal-sparing approaches for patients with rectal cancer who achieved a complete or major response following neoadjuvant therapy constitute a paradigm of a potential shift in the management of patients with rectal cancer; however, their role remains controversial. The aim of this study was to investigate the feasibility of rectal-sparing approaches to preserve the rectum without impairing the outcomes. METHODS: This prospective, multicenter, observational study investigated the outcomes of patients with clinical stage II-III mid-low rectal adenocarcinoma treated with any neoadjuvant therapy, and either transanal local excision or watch-and-wait approach, based on tumor response (major or complete) and patient/surgeon choice. The primary endpoint of the study was rectum preservation at a minimum follow-up of 2 years. Secondary endpoints were overall, disease-free, local and distant recurrence-free, and stoma-free survival at 3 years. RESULTS: Of the 178 patients enrolled in 16 centers, 112 (62.9%) were managed with local excision and 66 (37.1%) with watch-and-wait. At a median (interquartile range) follow-up of 36.1 (30.6-45.6) months, the rectum was preserved in 144 (80.9%) patients. The 3-year rectum-sparing, overall survival, disease-free survival, local recurrence-free survival, and distant recurrence-free survival was 80.6% (95% CI 73.9-85.8), 97.6% (95% CI 93.6-99.1), 90.0% (95% CI 84.3-93.7), 94.7% (95% CI 90.1-97.2), and 94.6% (95% CI 89.9-97.2), respectively. The 3-year stoma-free survival was 95.0% (95% CI 89.5-97.6). The 3-year regrowth-free survival in the watch-and-wait group was 71.8% (95% CI 59.9-81.2). CONCLUSIONS: In rectal cancer patients with major or complete clinical response after neoadjuvant therapy, the rectum can be preserved in about 80% of cases, without compromising the outcomes

Cancer screening in patients with acromegaly: a plea for a personalized approach and international registries

Acromegaly is a rare condition, and often diagnosis is delayed by several years, for most patients. Acromegaly is characterized by short and long-term respiratory, cardiovascular and metabolic comorbidities, with possible impact on mortality. In the last two decades, life expectancy has progressively increased in part due to a reduction in biochemically active disease, multidisciplinary treatment approaches and a reduction in complications, and the availability of new drugs. Of note, a leading cause of mortality, cardiovascular comorbidity, has been replaced by cancer(s). As such, neoplasms more frequently observed (colon, thyroid, breast, prostate, and stomach) in patients with acromegaly are receiving increased attention. Chronic exposure to increased growth hormone serum levels may contribute to an increase in the occurrence and progression of cancers. Various efforts have been made to determine the pathogenetic mechanisms involved. However, there are no clear medical-related societal agreement(s) in relation to screening methods or timing regarding neoplasm(s) diagnosis in patients with acromegaly. Additionally, independent and dependent risk factor data in patients with acromegaly is lacking. International/national registries could help lay the groundwork to better study the impact of cancer(s) in patients with acromegaly and subsequently lead to and validate the most appropriate diagnostic and therapeutic path forward

Auto-segmentation of pelvic organs at risk on 0.35T MRI using 2D and 3D Generative Adversarial Network models

Purpose: Manual recontouring of targets and Organs At Risk (OARs) is a time-consuming and operator-dependent task. We explored the potential of Generative Adversarial Networks (GAN) to auto-segment the rectum, bladder and femoral heads on 0.35T MRIs to accelerate the online MRI-guided-Radiotherapy (MRIgRT) workflow. Methods: 3D planning MRIs from 60 prostate cancer patients treated with 0.35T MR-Linac were collected. A 3D GAN architecture and its equivalent 2D version were trained, validated and tested on 40, 10 and 10 patients respectively. The volumetric Dice Similarity Coefficient (DSC) and 95th percentile Hausdorff Distance (HD95th) were computed against expert drawn ground-truth delineations. The networks were also validated on an independent external dataset of 16 patients. Results: In the internal test set, the 3D and 2D GANs showed DSC/HD95th of 0.83/9.72 mm and 0.81/10.65 mm for the rectum, 0.92/5.91 mm and 0.85/15.72 mm for the bladder, and 0.94/3.62 mm and 0.90/9.49 mm for the femoral heads. In the external test set, the performance was 0.74/31.13 mm and 0.72/25.07 mm for the rectum, 0.92/9.46 mm and 0.88/11.28 mm for the bladder, and 0.89/7.00 mm and 0.88/10.06 mm for the femoral heads. The 3D and 2D GANs required on average 1.44 s and 6.59 s respectively to generate the OARs’ volumetric segmentation for a single patient. Conclusions: The proposed 3D GAN auto-segments pelvic OARs with high accuracy on 0.35T, in both the internal and the external test sets, outperforming its 2D equivalent in both segmentation robustness and volume generation time

Trouillas’s Grading and Post-Surgical Tumor Residue Assessment in Pituitary Adenomas: The Importance of the Multidisciplinary Approach

Background: We aim to assess the role of a multidisciplinary approach in pituitary adenomas (PitNETs) classification, evaluate criteria concordance, and compare intraoperative assessments with post-operative MRIs for tumor remnants. Methods: Clinical, radiological, histological, and intra- and post-operative data of the treated PitNETs were extracted from prospectively created records. PitNETs were graded according to Trouillas, and the evaluation of the tumor remnants was recorded. Results: Of 362 PitNETs, 306 underwent surgery, with Trouillas grading assigned to 296. Eight-nine radiologically non-invasive PitNETs progressed to grades 1b (27), 2a (42), or 2b (20) due to proliferative or surgical invasiveness criteria. Twenty-six radiologically invasive tumors were graded 2b due to proliferative criteria. Surgical resection details and post-surgical MRI findings revealed that residual tumors were more common in grades 2a and 2b. During surgery, small tumor remnants were documented in 14 patients which were not visible on post-surgical MRI. Post-surgical MRIs identified remnants in 19 PitNETs not seen during surgery, located in lateral recesses of the sella (4), retrosellar (2), or suprasellar regions (7), along the medial wall of the cavernous sinus (6). Conclusions: The Pituitary Board allows for the correct grading of PitNETs to be obtained and an accurate identification of high-risk patients who should undergo closer surveillance due to tumor remnants

The Role of Testosterone in Spermatogenesis: lessons from proteome profiling of human spermatozoa in testosterone deficiency

Testosterone is essential to maintain qualitative spermatogenesis. Nonetheless, no studies have been yet performed in humans to analyze the testosterone-mediated expression of sperm proteins and their importance in reproduction. Thus, this study aimed to identify sperm protein alterations in male hypogonadism using proteomic profiling. We have performed a comparative proteomic analysis comparing sperm from fertile controls (a pool of 5 normogonadic normozoospermic fertile men) versus sperm from patients with secondary hypogonadism (a pool of 5 oligozoospermic hypogonadic patients due to isolated LH deficiency). Sperm protein composition was analyzed, after peptide labelling with Isobaric Tags, via liquid chromatography followed by tandem mass spectrometry (LC-MS/MS) on an LTQ Velos-Orbitrap mass spectrometer. LC-MS/MS data were analyzed using Proteome Discoverer. Criteria used to accept protein identification included a false discovery rate (FDR) of 1% and at least 1 peptide match per protein. Up to 986 proteins were identified and, of those, 43 proteins were differentially expressed: 32 proteins were under-expressed and 11 were over-expressed in the pool of hypogonadic patients compared to the controls. Bioinformatic analyses were performed using UniProt Knowledgebase, and the Gene Ontology Consortium database based on PANTHER. Notably, 13 of these 43 differentially expressed proteins have been previously reported to be related to sperm function and spermatogenesis. Western blot analyses for A-Kinase Anchoring Protein 3 (AKAP3) and the Prolactin Inducible Protein (PIP) were used to confirm the proteomics data. In summary, a high-resolution mass spectrometry-based proteomic approach was used for the first time to describe alterations of the sperm proteome in secondary male hypogonadism. Some of the differential sperm proteins described in this study, which include Prosaposin, SMOC-1, SERPINA5, SPANXB1, GSG1, ELSPBP1, fibronectin, 5-oxoprolinase, AKAP3, AKAP4, HYDIN, ROPN1B, ß-Microseminoprotein and Protein S100-A8, could represent new targets for the design of infertility treatments due to androgen deficiency