Deep learning for dual detection of microsatellite instability and POLE mutations in colorectal cancer histopathology.

In the spectrum of colorectal tumors, microsatellite-stable (MSS) tumors with DNA polymerase ε (POLE) mutations exhibit a hypermutated profile, holding the potential to respond to immunotherapy similarly to their microsatellite-instable (MSI) counterparts. Yet, due to their rarity and the associated testing costs, systematic screening for these mutations is not commonly pursued. Notably, the histopathological phenotype resulting from POLE mutations is theorized to resemble that of MSI. This resemblance not only could facilitate their detection by a transformer-based Deep Learning (DL) system trained on MSI pathology slides, but also indicates the possibility for MSS patients with POLE mutations to access enhanced treatment options, which might otherwise be overlooked. To harness this potential, we trained a Deep Learning classifier on a large dataset with the ground truth for microsatellite status and subsequently validated its capabilities for MSI and POLE detection across three external cohorts. Our model accurately identified MSI status in both the internal and external resection cohorts using pathology images alone. Notably, with a classification threshold of 0.5, over 75% of POLE driver mutant patients in the external resection cohorts were flagged as "positive" by a DL system trained on MSI status. In a clinical setting, deploying this DL model as a preliminary screening tool could facilitate the efficient identification of clinically relevant MSI and POLE mutations in colorectal tumors, in one go.

Erdosteine in children and adults with bronchiectasis (BETTER trial): study protocol for a multicentre, double-blind, randomised controlled trial.

INTRODUCTION: Bronchiectasis is a worldwide chronic lung disorder where exacerbations are common. It affects people of all ages, but especially Indigenous populations in high-income nations. Despite being a major contributor to chronic lung disease, there are no licensed therapies for bronchiectasis and there remain relatively few randomised controlled trials (RCTs) conducted in children and adults. Our RCT will address some of these unmet needs by evaluating whether the novel mucoactive agent, erdosteine, has a therapeutic role in children and adults with bronchiectasis.Our primary aim is to determine in children and adults aged 2-49 years with bronchiectasis whether regular erdosteine over a 12-month period reduces acute respiratory exacerbations compared with placebo. Our primary hypothesis is that people with bronchiectasis who regularly use erdosteine will have fewer exacerbations than those receiving placebo.Our secondary aims are to determine the effect of the trial medications on quality of life (QoL) and other clinical outcomes (exacerbation duration, time-to-next exacerbation, hospitalisations, lung function, adverse events). We will also assess the cost-effectiveness of the intervention. METHODS AND ANALYSIS: We are undertaking an international multicentre, double-blind, placebo-RCT to evaluate whether 12 months of erdosteine is beneficial for children and adults with bronchiectasis. We will recruit 194 children and adults with bronchiectasis to a parallel, superiority RCT at eight sites across Australia, Malaysia and Philippines. Our primary endpoint is the rate of exacerbations over 12 months. Our main secondary outcomes are QoL, exacerbation duration, time-to-next exacerbation, hospitalisations and lung function. ETHICS AND DISSEMINATION: The Human Research Ethics Committees (HREC) of Children's Health Queensland (for all Australian sites), University of Malaya Medical Centre (Malaysia) and St. Luke's Medical Centre (Philippines) approved the study. We will publish the results and share the outcomes with the academic and medical community, funding and relevant patient organisations. TRIAL REGISTRATION NUMBER: ACTRN12621000315819.

Effect of repeated post-resistance exercise cold or hot water immersion on in-season inflammatory responses in academy rugby players: a randomised controlled cross-over design.

PURPOSE: Uncertainty exists if post-resistance exercise hydrotherapy attenuates chronic inflammatory and hormone responses. The effects of repeated post-resistance exercise water immersion on inflammatory and hormone responses in athletes were investigated. METHODS: Male, academy Super Rugby players (n = 18, 19.9 ± 1.5 y, 1.85 ± 0.06 m, 98.3 ± 10.7 kg) participated in a 12-week programme divided into 3 × 4-week blocks of post-resistance exercise water immersion (either, no immersion control [CON]; cold [CWI]; or hot [HWI] water immersion), utilising a randomised cross-over pre-post design. Fasted, morning blood measures were collected prior to commencement of first intervention block, and every fourth week thereafter. Linear mixed-effects models were used to analyse main (treatment, time) and interaction effects. RESULTS: Repeated CWI (p = 0.025, g = 0.05) and HWI (p < 0.001, g = 0.62) reduced creatine kinase (CK), compared to CON. HWI decreased (p = 0.013, g = 0.59) interleukin (IL)-1ra, compared to CON. HWI increased (p < 0.001-0.026, g = 0.06-0.17) growth factors (PDGF-BB, IGF-1), compared to CON and CWI. CWI increased (p = 0.004, g = 0.46) heat shock protein-72 (HSP-72), compared to HWI. CONCLUSION: Post-resistance exercise CWI or HWI resulted in trivial and moderate reductions in CK, respectively, which may be partly due to hydrostatic effects of water immersion. Post-resistance exercise HWI moderately decreased IL-1ra, which may be associated with post-resistance exercise skeletal muscle inflammation influencing chronic resistance exercise adaptive responses. Following post-resistance exercise water immersion, CWI increased HSP-72 suggesting a thermoregulatory response indicating improved adaptive inflammatory responses to temperature changes, while HWI increased growth factors (PDGF-BB, IGF-1) indicating different systematic signalling pathway activation. Our data supports the continued use of post-resistance exercise water immersion recovery strategies of any temperature during in-season competition phases for improved inflammatory adaptive responses in athletes.

Digital Spatial Profiling Identifies Distinct Molecular Signatures of Vascular Lesions in Pulmonary Arterial Hypertension.

RATIONALE: Idiopathic Pulmonary Arterial Hypertension (IPAH) is characterized by extensive pulmonary vascular remodeling due to plexiform and obliterative lesions, media hypertrophy, inflammatory cell infiltration, and alterations of the adventitia. OBJECTIVE: Test the hypothesis that microscopic IPAH vascular lesions express unique molecular profiles, which collectively are different from control pulmonary arteries. METHODS: We used digital spatial transcriptomics to profile the genome-wide differential transcriptomic signature of key pathological lesions (plexiform, obliterative, intima+media hypertrophy, and adventitia) in IPAH lungs (n= 11) and compared these data to the intima+media and adventitia of control pulmonary artery (n=5). RESULTS: We detected 8273 transcripts in the IPAH lesions and control lung pulmonary arteries. Plexiform lesions and IPAH adventitia exhibited the greatest number of differentially expressed genes when compared with intima-media hypertrophy and obliterative lesions. Plexiform lesions in IPAH showed enrichment for (i) genes associated with TGFß-signaling and (ii) mutated genes affecting the extracellular matrix and endothelial-mesenchymal transformation. Plexiform lesions and IPAH adventitia showed upregulation of genes involved in immune and interferon signaling, coagulation, and complement pathways. Cellular deconvolution indicated variability in the number of vascular and inflammatory cells between IPAH lesions, which underlies the differential transcript profiling. CONCLUSIONS: IPAH lesions express unique molecular transcript profiles enriched for pathways involving pathogenetic pathways, including genetic disease drivers, innate and acquired immunity, hypoxia sensing, and angiogenesis signaling. These data provide a rich molecular-structural framework in IPAH vascular lesions that inform novel biomarkers and therapeutic targets in this highly morbid disease.

Gut Microbiome and Metabolic and Immune Indices in Males with or without Evidence of Metabolic Dysregulation.

Background: The contributions of the gut microbiota to obesity and metabolic disease represent a potentially modifiable factor that may explain variation in risk between individuals. This study aimed to explore relationships among microbial composition and imputed functional attributes, a range of soluble metabolic and immune indices, and gene expression markers in males with or without evidence of metabolic dysregulation (MetDys). Methods: This case-control study included healthy males (n=15; 41.9±11.7 years; body mass index [BMI], 22.9±1.2 kg/m2) and males with evidence of MetDys (n=14; 46.6±10.0 years; BMI, 35.1±3.3 kg/m2) who provided blood and faecal samples for assessment of a range of metabolic and immune markers and microbial composition using 16S rRNA gene sequencing. Metagenomic functions were imputed from microbial sequence data for analysis. Results: In addition to elevated values in a range of traditional metabolic, adipokine and inflammatory indices in the MetDys group, 23 immunomodulatory genes were significantly altered in the MetDys group. Overall microbial diversity did not differ between groups; however, a trend for a higher relative abundance of the Bacteroidetes (P=0.06) and a lower relative abundance of the Verrucomicrobia (P=0.09) phyla was noted in the MetDys group. Using both family- and genera-level classifications, a partial least square discriminant analysis revealed unique microbial signatures between the groups. Conclusion: These findings confirm the need for ongoing investigations in human clinical cohorts to further resolve the relationships between the gut microbiota and metabolic and immune markers and risk for metabolic disease.

TcrXY is an acid-sensing two-component transcriptional regulator of Mycobacterium tuberculosis required for persistent infection.

The ability of Mycobacterium tuberculosis (Mtb) to persist in the host complicates and prolongs tuberculosis (TB) patient chemotherapy. Here we demonstrate that a neglected two-component system (TCS) of Mtb, TcrXY, is an autoregulated acid-sensing TCS that controls a functionally diverse 70-gene regulon required for bacterial persistence. Characterisation of two representatives of this regulon, Rv3706c and Rv3705A, implicate these genes as key determinants for the survival of Mtb in vivo by serving as important effectors to mitigate redox stress at acidic pH. We show that genetic silencing of the response regulator tcrX using CRISPR interference attenuates the persistence of Mtb during chronic mouse infection and improves treatment with the two front-line anti-TB drugs, rifampicin and isoniazid. We propose that targeting TcrXY signal transduction blocks the ability of Mtb to sense and respond to acid stress, resulting in a disordered program of persistence to render the organism vulnerable to existing TB chemotherapy.

Synthesis of steroidal inhibitors for Mycobacterium tuberculosis.

Oxidised derivatives of cholesterol have been shown to inhibit the growth of Mycobacterium tuberculosis (Mtb). The bacteriostatic activity of these compounds has been attributed to their inhibition of CYP125A1 and CYP142A1, two metabolically critical cytochromes P450 that initiate degradation of the sterol side chain. Here, we synthesise and characterise an extensive library of 28 cholesterol derivatives to develop a structure-activity relationship for this class of inhibitors. The candidate compounds were evaluated for MIC with virulent Mtb and in binding studies with CYP125A1 and CYP142A1 from Mtb.

Automated curation of large-scale cancer histopathology image datasets using deep learning.

BACKGROUND: Artificial intelligence (AI) has numerous applications in pathology, supporting diagnosis and prognostication in cancer. However, most AI models are trained on highly selected data, typically one tissue slide per patient. In reality, especially for large surgical resection specimens, dozens of slides can be available for each patient. Manually sorting and labelling whole-slide images (WSIs) is a very time-consuming process, hindering the direct application of AI on the collected tissue samples from large cohorts. In this study we addressed this issue by developing a deep-learning (DL)-based method for automatic curation of large pathology datasets with several slides per patient. METHODS: We collected multiple large multicentric datasets of colorectal cancer histopathological slides from the United Kingdom (FOXTROT, N = 21,384 slides; CR07, N = 7985 slides) and Germany (DACHS, N = 3606 slides). These datasets contained multiple types of tissue slides, including bowel resection specimens, endoscopic biopsies, lymph node resections, immunohistochemistry-stained slides, and tissue microarrays. We developed, trained, and tested a deep convolutional neural network model to predict the type of slide from the slide overview (thumbnail) image. The primary statistical endpoint was the macro-averaged area under the receiver operating curve (AUROCs) for detection of the type of slide. RESULTS: In the primary dataset (FOXTROT), with an AUROC of 0.995 [95% confidence interval [CI]: 0.994-0.996] the algorithm achieved a high classification performance and was able to accurately predict the type of slide from the thumbnail image alone. In the two external test cohorts (CR07, DACHS) AUROCs of 0.982 [95% CI: 0.979-0.985] and 0.875 [95% CI: 0.864-0.887] were observed, which indicates the generalizability of the trained model on unseen datasets. With a confidence threshold of 0.95, the model reached an accuracy of 94.6% (7331 classified cases) in CR07 and 85.1% (2752 classified cases) for the DACHS cohort. CONCLUSION: Our findings show that using the low-resolution thumbnail image is sufficient to accurately classify the type of slide in digital pathology. This can support researchers to make the vast resource of existing pathology archives accessible to modern AI models with only minimal manual annotations.

Mycobacterium tuberculosis Deficient in PdtaS Cytosolic Histidine Kinase Displays Attenuated Growth and Affords Protective Efficacy against Aerosol M. tuberculosis Infection in Mice.

New control measures are urgently required to control tuberculosis (TB), as the current vaccine, Bacille Calmette-Guérin (BCG), has had a limited impact on disease spread. The identification of virulence mechanisms of Mycobacterium tuberculosis is an important strategy in vaccine design, as it permits the development of strains attenuated for growth that may have vaccine potential. In this report, we determined the role of the PdtaS response regulator in M. tuberculosis virulence and defined the vaccine potential of a pdtaS-deficient strain. Deletion of pdtaS (MtbΔpdtaS) resulted in reduced persistence of M. tuberculosis within mouse organs, which was equivalent to the persistence of the BCG vaccine in the lung and liver of infected mice. However, the generation of effector CD4+ and CD8+ T cells (CD44+CD62LloKLRG1+) was similar between wild-type M. tuberculosis and MtbΔpdtaS and greater than that elicited by BCG. Heightened immunity induced by MtbΔpdtaS compared to BCG was also observed by analysis of antigen-specific IFN-γ-secreting T cell responses induced by vaccination. MtbΔpdtaS displayed improved protection against aerosol M. tuberculosis compared to BCG, which was most apparent in the lung at 20 weeks post-infection. These results suggest that the deletion of the PdtaS response regulator warrants further appraisal as a tool to combat TB in humans.

Reassessing the putative molecular Target(s) of potent antitubercular 2-(Alkylsulfonyl)acetamides.

Simple alkyl-sulfonylacetamides have potent antitubercular activity and significantly decrease mycolic acid levels in mycobacteria. Although these compounds were originally designed to inhibit the ketoacyl synthase domain of fatty acid synthase, structure-activity relationships and biochemical evidence do not fully support fatty acid synthase as the target. In 2004, an enzyme family involved in the activation and transfer of fatty acids as acyl-adenylates was identified in mycobacteria, separate from the universal acetyl-CoA carrier mechanism. These fatty acyl-AMP ligases (FAAL), encoded by the FadD family play important roles in the biosynthesis of mycolic acids along with fatty acid metabolism and are hypothesised here to be the molecular target of the sulfonylacetamides. Due to structural similarities with the ligase's natural substrate, it is believed these compounds are exerting action via competitive inhibition of these highly potent molecular targets. The primary aim of this investigation was to synthesize an extended library of sulfonylacetamide derivatives, building upon existing structural activity relations to validate the molecular mechanism with the aid of molecular modelling, while also attempting to explore novel structural isosteres for further drug design and development. Sulfonylacetamide derivatives were modified based on the putative molecular target resulting in derivatives with improved activities towards Mycobacteriumtuberculosis (H37Rv). The most active novel derivatives reported were 19, 22b, 22c and 46 displaying MIC90 levels of 1.4, 16.0, 13.0 and 5.9 µg/mL, respectively.

seco-1-Azacubane-2-carboxylic Acid: Derivative Scope and Comparative Biological Evaluation.

The unusual and sterically constrained amino acid, seco-1-azacubane-2-carboxylic acid, was incorporated into a range of bioactive chemical templates, including enalaprilat, perindoprilat, endomorphin-2 and isoniazid, and subjected to biological testing. The endomorphin-2 derivative displayed increased activity at the δ opioid receptor, but a loss in activity was observed in the other cases, although human normal cell line evaluation suggests limited cytotoxic effects.

End-to-end prognostication in colorectal cancer by deep learning: a retrospective, multicentre study.

BACKGROUND: Precise prognosis prediction in patients with colorectal cancer (ie, forecasting survival) is pivotal for individualised treatment and care. Histopathological tissue slides of colorectal cancer specimens contain rich prognostically relevant information. However, existing studies do not have multicentre external validation with real-world sample processing protocols, and algorithms are not yet widely used in clinical routine. METHODS: In this retrospective, multicentre study, we collected tissue samples from four groups of patients with resected colorectal cancer from Australia, Germany, and the USA. We developed and externally validated a deep learning-based prognostic-stratification system for automatic prediction of overall and cancer-specific survival in patients with resected colorectal cancer. We used the model-predicted risk scores to stratify patients into different risk groups and compared survival outcomes between these groups. Additionally, we evaluated the prognostic value of these risk groups after adjusting for established prognostic variables. FINDINGS: We trained and validated our model on a total of 4428 patients. We found that patients could be divided into high-risk and low-risk groups on the basis of the deep learning-based risk score. On the internal test set, the group with a high-risk score had a worse prognosis than the group with a low-risk score, as reflected by a hazard ratio (HR) of 4·50 (95% CI 3·33-6·09) for overall survival and 8·35 (5·06-13·78) for disease-specific survival (DSS). We found consistent performance across three large external test sets. In a test set of 1395 patients, the high-risk group had a lower DSS than the low-risk group, with an HR of 3·08 (2·44-3·89). In two additional test sets, the HRs for DSS were 2·23 (1·23-4·04) and 3·07 (1·78-5·3). We showed that the prognostic value of the deep learning-based risk score is independent of established clinical risk factors. INTERPRETATION: Our findings indicate that attention-based self-supervised deep learning can robustly offer a prognosis on clinical outcomes in patients with colorectal cancer, generalising across different populations and serving as a potentially new prognostic tool in clinical decision making for colorectal cancer management. We release all source codes and trained models under an open-source licence, allowing other researchers to reuse and build upon our work. FUNDING: The German Federal Ministry of Health, the Max-Eder-Programme of German Cancer Aid, the German Federal Ministry of Education and Research, the German Academic Exchange Service, and the EU.

Encrypted federated learning for secure decentralized collaboration in cancer image analysis.

Artificial intelligence (AI) has a multitude of applications in cancer research and oncology. However, the training of AI systems is impeded by the limited availability of large datasets due to data protection requirements and other regulatory obstacles. Federated and swarm learning represent possible solutions to this problem by collaboratively training AI models while avoiding data transfer. However, in these decentralized methods, weight updates are still transferred to the aggregation server for merging the models. This leaves the possibility for a breach of data privacy, for example by model inversion or membership inference attacks by untrusted servers. Somewhat-homomorphically-encrypted federated learning (SHEFL) is a solution to this problem because only encrypted weights are transferred, and model updates are performed in the encrypted space. Here, we demonstrate the first successful implementation of SHEFL in a range of clinically relevant tasks in cancer image analysis on multicentric datasets in radiology and histopathology. We show that SHEFL enables the training of AI models which outperform locally trained models and perform on par with models which are centrally trained. In the future, SHEFL can enable multiple institutions to co-train AI models without forsaking data governance and without ever transmitting any decryptable data to untrusted servers.

Allan William Cripps: a mucosal immunologist and mentor from beginning to end.

Allan Cripps was internationally recognized in the field of mucosal immunology, in particular the relationship between respiratory diseases and mucosal immunization strategies. Allan's career spanned scientific and applied research, commercialization, health education, and evolved into leadership roles in public-health and academic administration. Allan published over 400 papers and mentored over 40 research higher degree candidates. Allan was renowned for his mentorship, that did not end with the awarding of a PhD or Master's degree, but continued across a lifetime of professional engagement. Allan's key contributions to immunology included characterizing the ontogeny of the human mucosal immune system, understanding the impact of respiratory infections and otitis media in children, developing diagnostic technologies and mucosal vaccine strategies, and identifying the roles of the common mucosal immune system in human health. In this biography for the 100th anniversary of the Journal, we follow his journey of discovery and contributions to immunological research.

Macroscopic Evaluation of Colon Cancer Resection Specimens.

Colon cancer is a common disease internationally. Outcomes have not improved to the same degree as in rectal cancer, where the focus on total mesorectal excision and pathological feedback has significantly contributed to improved survival and reduced local recurrence. Colon cancer surgery shows significant variation around the world, with differences in mesocolic integrity, height of the vascular ligation and length of the bowel resected. This leads to variation in well-recognised quality measures like lymph node yield. Pathologists are able to assess all of these variables and are ideally placed to provide feedback to surgeons and the wider multidisciplinary team to improve surgical quality over time. With a move towards complete mesocolic excision with central vascular ligation to remove the primary tumour and all mechanisms of spread within an intact package, pathological feedback will be central to improving outcomes for patients with operable colon cancer. This review focusses on the key quality measures and the evidence that underpins them.

Transformer-based biomarker prediction from colorectal cancer histology: A large-scale multicentric study.

Deep learning (DL) can accelerate the prediction of prognostic biomarkers from routine pathology slides in colorectal cancer (CRC). However, current approaches rely on convolutional neural networks (CNNs) and have mostly been validated on small patient cohorts. Here, we develop a new transformer-based pipeline for end-to-end biomarker prediction from pathology slides by combining a pre-trained transformer encoder with a transformer network for patch aggregation. Our transformer-based approach substantially improves the performance, generalizability, data efficiency, and interpretability as compared with current state-of-the-art algorithms. After training and evaluating on a large multicenter cohort of over 13,000 patients from 16 colorectal cancer cohorts, we achieve a sensitivity of 0.99 with a negative predictive value of over 0.99 for prediction of microsatellite instability (MSI) on surgical resection specimens. We demonstrate that resection specimen-only training reaches clinical-grade performance on endoscopic biopsy tissue, solving a long-standing diagnostic problem.

Comparison of four DNA extraction methods for 16s rRNA microbiota profiling of human faecal samples.

OBJECTIVE: Growth in large population-based studies assessing contributions of the gut microbiota to health and disease requires high-throughput sample processing and analysis methods. This study assessed the impact that modifications to a commercially available magnetic bead based, semi-automated DNA extraction kit had on determination of microbial composition, relative to an established in-house method involving a combination of mechanical and chemical lysis. DNA was extracted from faecal samples from healthy adults (n = 12; 34-69 years), microbial composition was determined by V3-V4 16s rRNA sequencing and compared between extraction methods. RESULTS: Diversity metrics did not differ between extraction methods. Differences in the relative abundance of key phyla, including a significantly lower abundance of the Firmicutes (p = 0.004) and higher relative abundance of the Bacteroidetes (p = 0.005) and Proteobacteria (p = 0.008) phyla were noted where the DNA extraction did not include additional chemical and mechanical lysis. Principal coordinate analysis of family and genera level data also suggested a potential for sample pre-processing to impact microbial composition. Observations of the potential for skewed microbial composition profiles from samples prepared using a semi-automated DNA extraction kit without additional sample pre-processing highlights a need for consideration of standardisation of methodological approaches to increase the comparability of microbial compositional data.

The impact of mismatch repair status and systemic inflammatory markers on radiological staging in colon cancer.

OBJECTIVE: Mismatch repair (MMR) deficient (dMMR) colon cancer (CC) is distinct from MMR proficient (pMMR) CC, yet the impact of MMR status on radiological staging is unclear. The purpose of this study was to investigate how MMR status impacts CC CT staging. METHODS: We retrospectively compared CT staging accuracy between dMMR and pMMR CC patients undergoing curative resection. Accuracy was assessed as individual tumour (T)/nodal (N) stages and as dichotomous "statuses" (T1/2 vs T3/4; N0 vs N1/2). Patient characteristics were analysed for factors to support staging. RESULTS: There was no significant difference in overall staging accuracy between the dMMR (44 patients) and pMMR (57 patients) groups. dMMR tumours with incorrect N stage/"status" were more likely to be overstaged than pMMR tumours (90% vs 59%; p = 0.023 for "N status"). Platelet count, CRP and neutrophil count (AUC 0.76 (p = 0.0078), 0.75 (p = 0.034) and 0.70 (p = 0.044), respectively) were associated with "N status" in dMMR tumours. CONCLUSION: Whilst overall staging accuracy was similar between groups, incorrectly N staged dMMR tumours were more likely to be overstaged than pMMR tumours, risking inappropriate surgical or neoadjuvant treatment. We describe novel relationships between several inflammatory markers and pathological "N status" in dMMR CC, which if integrated into routine practice may improve CT staging accuracy. ADVANCES IN KNOWLEDGE: Compared to pMMR CC, dMMR CC is at significant risk of N overstaging. Platelet count, CRP and neutrophil count are higher in dMMR CC patients with nodal metastases than those without, and their role in refining clinical staging requires further investigation.

Associations between AI-Assisted Tumor Amphiregulin and Epiregulin IHC and Outcomes from Anti-EGFR Therapy in the Routine Management of Metastatic Colorectal Cancer.

PURPOSE: High tumor production of the EGFR ligands, amphiregulin (AREG) and epiregulin (EREG), predicted benefit from anti-EGFR therapy for metastatic colorectal cancer (mCRC) in a retrospective analysis of clinical trial data. Here, AREG/EREG IHC was analyzed in a cohort of patients who received anti-EGFR therapy as part of routine care, including key clinical contexts not investigated in the previous analysis. EXPERIMENTAL DESIGN: Patients who received panitumumab or cetuximab ± chemotherapy for treatment of RAS wild-type mCRC at eight UK cancer centers were eligible. Archival formalin-fixed paraffin-embedded tumor tissue was analyzed for AREG and EREG IHC in six regional laboratories using previously developed artificial intelligence technologies. Primary endpoints were progression-free survival (PFS) and overall survival (OS). RESULTS: A total of 494 of 541 patients (91.3%) had adequate tissue for analysis. A total of 45 were excluded after central extended RAS testing, leaving 449 patients in the primary analysis population. After adjustment for additional prognostic factors, high AREG/EREG expression (n = 360; 80.2%) was associated with significantly prolonged PFS [median: 8.5 vs. 4.4 months; HR, 0.73; 95% confidence interval (CI), 0.56-0.95; P = 0.02] and OS [median: 16.4 vs. 8.9 months; HR, 0.66 95% CI, 0.50-0.86; P = 0.002]. The significant OS benefit was maintained among patients with right primary tumor location (PTL), those receiving cetuximab or panitumumab, those with an oxaliplatin- or irinotecan-based chemotherapy backbone, and those with tumor tissue obtained by biopsy or surgical resection. CONCLUSIONS: High tumor AREG/EREG expression was associated with superior survival outcomes from anti-EGFR therapy in mCRC, including in right PTL disease. AREG/EREG IHC assessment could aid therapeutic decisions in routine practice. See related commentary by Randon and Pietrantonio, p. 4021.

Assessment of a Multispecies Probiotic Supplement for Relief of Seasonal Allergic Rhinitis: A Randomized Double-Blind Placebo-Controlled Trial.

Background: Early phase clinical research provided initial support for the use of a multispecies probiotic supplement to improve quality of life (QoL) in adults with seasonal allergic rhinitis (AR) and reduce the use of AR symptom relieving medication. This study aimed to confirm these early phase findings in a double-blind randomized placebo-controlled trial. Methods: Individuals, aged 18-65 years, with a minimum 2-year history of AR, moderate-to-severe AR symptoms, and a positive radio-allergosorbent test to Bermuda (Couch) Grass were randomized to receive either a multispecies probiotic supplement (total colony-forming units 4 × 109/day) or placebo twice daily for 8 weeks. A mini-rhinoconjunctivitis quality of life questionnaire (mRQLQ) scale was administered at screening, days 0, 28, and 56. The proportion of participants with a >0.7 improvement in mRQLQ was the primary outcome. Participants also completed a daily symptom and medication diary during the supplementation period. Results: There were 165 participants randomized, with 142 included in the primary outcome analysis. The percentage of participants meeting the threshold for a clinically meaningful reduction in the mRQLQ from days 0 to 56 was not significantly different between groups (61% vs. 62%, p = 0.90). However, 76 participants had a clinically meaningful improvement in QoL (decrease in mRQLQ >0.7) prior to the start of supplementation (screening to day 0). Conclusion: Changes in self-reported QoL and other disease severity metrics between screening and the start of supplementation limited the ability to discern an effect of supplementation and highlight the need for adaptive clinical trial designs in allergy research. Clinical Trial Registration: The trial was registered with the Australia and New Zealand Clinical Trials Registry (ACTRN12619001319167).