The ypT may better predict the efficacy of neoadjuvant chemoradiotherapy than tumor regression grade in locally advanced rectal cancer patients diagnosed ypT1-4N0 / El ypT puede predecir mejor la eficacia de la quimiorradioterapia neoadyuvante que el grado de regresión tumoral en pacientes con cáncer de recto localmente avanzado diagnosticados ypT1-4N0

Purpose: This study aimed to assess the impact of ypT stage and tumor regression grade (TRG) on the long-term prognosis of patients with locally advanced rectal cancer (LARC) stage ypT1-4N0 after neoadjuvant chemoradiotherapy (NCRT). Methods: We retrospectively analyzed 585 patients with histologically diagnosed middle-low LARC (cT3-4 or cN + by pelvic MRI) from 2014 to 2019. All patients underwent NCRT, followed by total mesorectal excision. Disease-free survival (DFS) rates were compared among patients with different ypT stages and TRGs by Kaplan–Meier survival analysis. The chi-square test was used to analyze the relationship between clinicopathological or therapeutic factors and ypT stage. Results: The median follow‐up was 35.8 months (range 2.8–71.8 months). The 3-year DFS was 79.5%. A better 3-year DFS was achieved in patients with a pathologic complete response (94.0% vs. 74.3%, p < 0.001) and those in the ypT0-2 (86.5% vs. 66.6%, p < 0.001), ypN0 (85.0% vs. 60.2%, p < 0.001), and TRG0 + 1 (83.1% vs. 73.0%, p = 0.004) subgroups. A total of 309 patients (52.8%) achieved stage ypT1-4N0 after surgery. Among these patients, the ypT1-2N0 subgroup achieved a significantly higher 3-year DFS than the ypT3-4N0 subgroup (85.4% vs. 72.8%, p = 0.018); in contrast, the 3-year DFS did not significantly differ between the TRG1 and TRG2 + 3 subgroups (79.9% vs. 81.1%, p = 0.833). In the ypT1-2N0 or ypT3-4N0 subgroup, different TRG had no significant effect on failure patterns. Conclusions: For LARC patients with a ypT1-4N0 status after NCRT, ypT stage may be a more effective predictor of long-term prognosis than TRG.(AU)

Clinicopathological factors predict residual lymph node metastasis in locally advanced rectal cancer with ypT0-2 after neoadjuvant chemoradiotherapy.

PURPOSE: Residual lymph node metastases (RLNM) remained a great concern in the implementation of organ-preserving strategies and led to poor prognosis in locally advanced rectal cancer (LARC). In this study, we aimed to identify the clinicopathological factors correlated with RLNM in LARC patients with ypT0-2 after neoadjuvant chemoradiotherapy (NCRT). METHODS: We retrospectively analyzed 417 patients histologically diagnosed middle-low LARC after NCRT and total mesorectal excision (TME), whose pathological staging was ypT0-2. All patients received pelvic magnetic resonance imaging (MRI) before NCRT. The radiation doses were 50-50.6 Gy for the planning gross tumor volume and 41.8-45 Gy for the planning target volume, respectively. A nomogram for predicting RLNM was constructed using a binary logistic regression. Nomogram performance was assessed by receiver operating characteristic (ROC) curve, calibration curve, decision curve analysis (DCA) and clinical impact curve (CIC). RESULTS: After surgery, 191 patients (45.8%) were ypT0, 43 patients (10.3%) were ypT1 and 183 patients (43.9%) were ypT2, and a total of 49 patients (11.8%) were found the presence of RLNM. Multivariable analyses identified MRI-defined mesorectal fascia (MRF)-positive, high-grade histopathology at biopsy, advanced ypT-category, and the presence of perineural invasion (PNI) as the predictive factors. The nomogram, incorporating all these predictors, showed good discrimination and calibration efficacy, with the areas under the ROC curve of 0.690 (95% CI: 0.610-0.771). Both DCA and CIC demonstrated that this nomogram has good clinical usefulness. CONCLUSION: The nomogram model can predict RLNM in patients with ypT0-2 tumors. It can help select suitable patients for performing organ-preserving strategies after NCRT.

Effect of oxygen-containing functional group contents on sorption of lead ions by acrylate-functionalized hydrochar.

The surface functional groups of hydrochar are crucial to its surface properties, and their contents are strongly positively correlated with the adsorption performance. In this study, acrylate-functionalized hydrochar (AHC) with varying contents of O-containing functional groups (OFGs) was synthesized via hydrothermal carbonization (HTC) of bamboo, acrylic acid and an initiator, and then deprotonated with NaOH. The AHCs were analyzed by various characterization techniques. During HTC, the higher amount of acrylic acid added led to higher carbon, oxygen and carboxyl contents, and to the larger specific surface area and pore volume of AHC. The adsorption kinetics, isotherms, thermodynamic, ionic strength and pH effects of Pb(II) on AHC were studied. Adsorption isotherms and kinetics obeyed Langmuir and pseudo-second-order models, respectively, indicating adsorption is monolayer chemical process. The adsorptive ability was well linearly related to the OFG contents of AHC. When acrylic acid was added to 25 mL during HTC, the adsorbing ability of AHC over Pb(II) reached 193.90 mg g-1. Hence, direct HTC of acrylic acid, biomass and an initiator can prepare hydrochar with controllable OFG contents, which is a prospective adsorbent for treating metal cations.

Genomic hallmarks and therapeutic targets of ribosome biogenesis in cancer.

Hyperactive ribosome biogenesis (RiboSis) fuels unrestricted cell proliferation, whereas genomic hallmarks and therapeutic targets of RiboSis in cancers remain elusive, and efficient approaches to quantify RiboSis activity are still limited. Here, we have established an in silico approach to conveniently score RiboSis activity based on individual transcriptome data. By employing this novel approach and RNA-seq data of 14 645 samples from TCGA/GTEx dataset and 917 294 single-cell expression profiles across 13 cancer types, we observed the elevated activity of RiboSis in malignant cells of various human cancers, and high risk of severe outcomes in patients with high RiboSis activity. Our mining of pan-cancer multi-omics data characterized numerous molecular alterations of RiboSis, and unveiled the predominant somatic alteration in RiboSis genes was copy number variation. A total of 128 RiboSis genes, including EXOSC4, BOP1, RPLP0P6 and UTP23, were identified as potential therapeutic targets. Interestingly, we observed that the activity of RiboSis was associated with TP53 mutations, and hyperactive RiboSis was associated with poor outcomes in lung cancer patients without TP53 mutations, highlighting the importance of considering TP53 mutations during therapy by impairing RiboSis. Moreover, we predicted 23 compounds, including methotrexate and CX-5461, associated with the expression signature of RiboSis genes. The current study generates a comprehensive blueprint of molecular alterations in RiboSis genes across cancers, which provides a valuable resource for RiboSis-based anti-tumor therapy.

The ypT may better predict the efficacy of neoadjuvant chemoradiotherapy than tumor regression grade in locally advanced rectal cancer patients diagnosed ypT1-4N0.

PURPOSE: This study aimed to assess the impact of ypT stage and tumor regression grade (TRG) on the long-term prognosis of patients with locally advanced rectal cancer (LARC) stage ypT1-4N0 after neoadjuvant chemoradiotherapy (NCRT). METHODS: We retrospectively analyzed 585 patients with histologically diagnosed middle-low LARC (cT3-4 or cN + by pelvic MRI) from 2014 to 2019. All patients underwent NCRT, followed by total mesorectal excision. Disease-free survival (DFS) rates were compared among patients with different ypT stages and TRGs by Kaplan-Meier survival analysis. The chi-square test was used to analyze the relationship between clinicopathological or therapeutic factors and ypT stage. RESULTS: The median follow-up was 35.8 months (range 2.8-71.8 months). The 3-year DFS was 79.5%. A better 3-year DFS was achieved in patients with a pathologic complete response (94.0% vs. 74.3%, p < 0.001) and those in the ypT0-2 (86.5% vs. 66.6%, p < 0.001), ypN0 (85.0% vs. 60.2%, p < 0.001), and TRG0 + 1 (83.1% vs. 73.0%, p = 0.004) subgroups. A total of 309 patients (52.8%) achieved stage ypT1-4N0 after surgery. Among these patients, the ypT1-2N0 subgroup achieved a significantly higher 3-year DFS than the ypT3-4N0 subgroup (85.4% vs. 72.8%, p = 0.018); in contrast, the 3-year DFS did not significantly differ between the TRG1 and TRG2 + 3 subgroups (79.9% vs. 81.1%, p = 0.833). In the ypT1-2N0 or ypT3-4N0 subgroup, different TRG had no significant effect on failure patterns. CONCLUSIONS: For LARC patients with a ypT1-4N0 status after NCRT, ypT stage may be a more effective predictor of long-term prognosis than TRG.

KRAS status predicted by pretreatment MRI radiomics was associated with lung metastasis in locally advanced rectal cancer patients.

BACKGROUND: Mutated KRAS may indicate an invasive nature and predict prognosis in locally advanced rectal cancer (LARC). We aimed to establish a radiomic model using pretreatment T2W MRIs to predict KRAS status and explore the association between the KRAS status or model predictions and lung metastasis. METHODS: In this retrospective multicentre study, LARC patients from two institutions between January 2012 and January 2019 were randomly divided into training and testing cohorts. Least absolute shrinkage and selection operator (LASSO) regression and the support vector machine (SVM) classifier were utilized to select significant radiomic features and establish a prediction model, which was validated by radiomic score distribution and decision curve analysis. The association between the model stratification and lung metastasis was investigated by Cox regression and Kaplan‒Meier survival analysis; the results were compared by the log-rank test. RESULTS: Overall, 103 patients were enrolled (73 and 30 in the training and testing cohorts, respectively). The median follow-up was 38.1 months (interquartile range: 26.9, 49.4). The radiomic model had an area under the curve (AUC) of 0.983 in the training cohort and 0.814 in the testing cohort. Using a cut-off of 0.679 defined by the receiver operating characteristic (ROC) curve, patients with a high radiomic score (RS) had a higher risk for lung metastasis (HR 3.565, 95% CI 1.337, 9.505, p = 0.011), showing similar predictive performances for the mutant and wild-type KRAS groups (HR 3.225, 95% CI 1.249, 8.323, p = 0.016, IDI: 1.08%, p = 0.687; NRI 2.23%, p = 0.766). CONCLUSIONS: We established and validated a radiomic model for predicting KRAS status in LARC. Patients with high RS experienced more lung metastases. The model could noninvasively detect KRAS status and may help individualize clinical decision-making.

Trithiocyanurate-functionalized hydrochar for effectively removing methylene blue and Pb (II) cationic pollutants.

Functionalization can change the physicochemical properties of hydrochar and improve its ability to adsorb pollutants. Herein, a trithiocyanurate-functionalized hydrochar (TTHC) was obtained from acylation of chloroacetyl chloride and hydrochar and modification with trithiocyanuric acid in alkaline conditions. TTHC can efficiently remove cationic methylene blue (MB) and Pb(II) from wastewater. The removal can be expressed with pseudo-second-order kinetic and Langmuir models. The MB and Pb(II) removed uptakes by TTHC at 298 K exceeded 909.9 and 182.8 mg g-1 respectively, and the removal rates reached 90% and 98% within 120 min respectively. Characterizations show TTHC is functionalized with trithiocyanurate, and rich in thiolate and aromaticity, and tends to adsorb MB/Pb(II) via multiple adsorption mechanisms. After five sorption-desorption regeneration cycles, TTHC maintained 80% and 99% adsorption capacities for MB and Pb(II) respectively. Therefore, TTHC is a promising efficient sorbent for removing MB and Pb(II) from effluents.

Fatty acid metabolism decreased while sexual selection increased in brown rats spreading south.

For mammals that originate in the cold north, adapting to warmer environments is crucial for southwards invasion. The brown rat (Rattus norvegicus) originated in Northeast China and has become a global pest. R. n. humiliatus (RNH) spread from the northeast, where R. n. caraco (RNC) lives, to North China and diverged to form a subspecies. Genomic analyses revealed that subspecies differentiation was promoted by temperature but impeded by gene flow and that genes related to fatty acid metabolism were under the strongest selection. Transcriptome analyses revealed downregulated hepatic genes related to fatty acid metabolism and upregulated those related to pheromones in RNH vs. RNC. Similar patterns were observed in relation to cold/warm acclimation. RNH preferred mates with stronger pheromone signals intra-populationally and more genetic divergence inter-populationally. We concluded that RNH experienced reduced fat utilization and increased pheromone-mediated sexual selection during its invasion from the cold north to warm south.

Spatial transcriptomics delineates molecular features and cellular plasticity in lung adenocarcinoma progression.

Indolent (lepidic) and aggressive (micropapillary, solid, and poorly differentiated acinar) histologic subtypes often coexist within a tumor tissue of lung adenocarcinoma (LUAD), but the molecular features associated with different subtypes and their transitions remain elusive. Here, we combine spatial transcriptomics and multiplex immunohistochemistry to elucidate molecular characteristics and cellular plasticity of distinct histologic subtypes of LUAD. We delineate transcriptional reprogramming and dynamic cell signaling that determine subtype progression, especially hypoxia-induced regulatory network. Different histologic subtypes exhibit heterogeneity in dedifferentiation states. Additionally, our results show that macrophages are the most abundant cell type in LUAD, and identify different tumor-associated macrophage subpopulations that are unique to each histologic subtype, which might contribute to an immunosuppressive microenvironment. Our results provide a systematic landscape of molecular profiles that drive LUAD subtype progression, and demonstrate potentially novel therapeutic strategies and targets for invasive lung adenocarcinoma.

Comparative transcriptome characterization of esophageal squamous cell carcinoma and adenocarcinoma.

Background: Esophageal cancers are primarily categorized as esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC). While various (epi) genomic alterations associated with tumor development in ESCC and EAC have been documented, a comprehensive comparison of the transcriptomes in these two cancer subtypes remains lacking. Methods: We collected 551 gene expression profiles from publicly available sources, including normal, ESCC, and EAC tissues or cell lines. Subsequently, we conducted a systematic analysis to compare the transcriptomes of these samples at various levels, including gene expression, promoter activity, alternative splicing (AS), alternative polyadenylation (APA), and gene fusion. Results: Seven distinct cluster gene expression patterns were identified among the differentially expressed genes in normal, ESCC, and EAC tissues. These patterns were enriched in the PI3K-Akt signaling pathway and the activation of extracellular matrix organization and exhibited repression of epidermal development. Notably, we observed additional genes or unique expression levels enriched in these shared pathways and biological processes related to tumor development and immune activation. In addition to the differentially expressed genes, there was an enrichment of lncRNA co-expression networks and downregulation of promoter activity associated with the repression of epidermal development in both ESCC and EAC. This indicates a common feature between these two cancer subtypes. Furthermore, differential AS and APA patterns in ESCC and EAC appear to partially affect the expression of host genes associated with bacterial or viral infections in these subtypes. No gene fusions were observed between ESCC and EAC, thus highlighting the distinct molecular mechanisms underlying these two cancer subtypes. Conclusions: We conducted a comprehensive comparison of ESCC and EAC transcriptomes and uncovered shared and distinct transcriptomic signatures at multiple levels. These findings suggest that ESCC and EAC may exhibit common and unique mechanisms involved in tumorigenesis.

Genome-wide DNA methylation landscape of four Chinese populations and epigenetic variation linked to Tibetan high-altitude adaptation.

DNA methylation (DNAm) is one of the major epigenetic mechanisms in humans and is important in diverse cellular processes. The variation of DNAm in the human population is related to both genetic and environmental factors. However, the DNAm profiles have not been investigated in the Chinese population of diverse ethnicities. Here, we performed double-strand bisulfite sequencing (DSBS) for 32 Chinese individuals representing four major ethnic groups including Han Chinese, Tibetan, Zhuang, and Mongolian. We identified a total of 604,649 SNPs and quantified DNAm at more than 14 million CpGs in the population. We found global DNAm-based epigenetic structure is different from the genetic structure of the population, and ethnic difference only partially explains the variation of DNAm. Surprisingly, non-ethnic-specific DNAm variations showed stronger correlation with the global genetic divergence than these ethnic-specific DNAm. Differentially methylated regions (DMRs) among these ethnic groups were found around genes in diverse biological processes. Especially, these DMR-genes between Tibetan and non-Tibetans were enriched around high-altitude genes including EPAS1 and EGLN1, suggesting DNAm alteration plays an important role in high-altitude adaptation. Our results provide the first batch of epigenetic maps for Chinese populations and the first evidence of the association of epigenetic changes with Tibetans' high-altitude adaptation.

Facile solvent-free radical polymerization to prepare itaconate-functionalized hydrochar for efficient sorption of methylene blue and Pb(II).

An itaconate-functionalized hydrochar (IFHC) was prepared from one-step solvent-free radical copolymerization of bamboo hydrochar, itaconic acid, ammonium persulphate and sodium hydroxide in solvent-free environment, and was employed to absorb methylene blue (MB) and Pb(II) from wastewater. Characterizations show IFHC has rich carboxylate and tends to adsorb cationic contaminants. The largest adsorbed quantities of MB and Pb(II) by IFHC are up to 1036 and 291.8 mg·g-1 at 298 K respectively as per the Langmuir isotherm. Sorption of MB and Pb(II) onto IFHC can be expressed well by Langmuir isotherm and pseudo-2nd-order kinetics equations. The high sorption performance depends on the rich carboxylate, which can adsorb MB/Pb(II) through an electrostatic interaction/inner-surface complexation mechanism. The sorptive capacity of regenerated IFHC decreased below 10% after 5 desorption-resorption cycles. Thus, the solvent-free free radical copolymerization is an environmentally-friendly strategy to synthesize novel efficient sorbents that can clean cationic contaminants from wastewater.

Gut microbiota-mediated nucleotide synthesis attenuates the response to neoadjuvant chemoradiotherapy in rectal cancer.

Preoperative neoadjuvant chemoradiotherapy (nCRT) is a standard treatment for locally advanced rectal cancer (LARC) patients, yet little is known about the mediators underlying the heterogeneous patient response. In this longitudinal study, we performed 16S rRNA sequencing on 353 fecal specimens and find reduced microbial diversity after nCRT. Multi-omics data integration reveals that Bacteroides vulgatus-mediated nucleotide biosynthesis associates with nCRT resistance in LARC patients, and nonresponsive tumors are characterized by the upregulation of genes related to DNA repair and nucleoside transport. Nucleosides supplementation or B. vulgatus gavage protects cancer cells from the 5-fluorouracil or irradiation treatment. An analysis of 2,205 serum samples from 735 patients suggests that uric acid is a potential prognosis marker for LARC patients receiving nCRT. Our data unravel the role of intestinal microbiota-mediated nucleotide biosynthesis in the response of rectal tumors to nCRT, and highlight the importance of deciphering the cross-talk between cancer cells and gut microorganisms during cancer therapies.

MRI-based radiomics to predict neoadjuvant chemoradiotherapy outcomes in locally advanced rectal cancer: A multicenter study.

Background and purpose: Predicting tumour response would be useful for selecting patients with locally advanced rectal cancer (LARC) for organ preservation strategies. We aimed to develop and validate a prediction model for T downstaging (ypT0-2) in LARC patients after neoadjuvant chemoradiotherapy and to identify those who may benefit from consolidation chemotherapy. Materials and methods: cT3-4 LARC patients at three tertiary medical centers from January 2012 to January 2019 were retrospectively included, while a prospective cohort was recruited from June 2021 to March 2022. Eight filter (principal component analysis, least absolute shrinkage and selection operator, partial least-squares discriminant analysis, random forest)-classifier (support vector machine, logistic regression) models were established to select radiomic features. A nomogram combining radiomics and significant clinical features was developed and validated by calibration curve and decision curve analysis. Interaction test was conducted to investigate the consolidation chemotherapy benefits. Results: A total of 634 patients were included (426 in training cohort, 174 in testing cohort and 34 in prospective cohort). A radiomic prediction model using partial least-squares discriminant analysis and a support vector machine showed the best performance (AUC: 0.832 [training]; 0.763 [testing]). A nomogram combining radiomics and clinical features showed significantly better prognostic performance (AUC: 0.842 [training]; 0.809 [testing]) than the radiomic model. The model was also tested in the prospective cohort with AUC 0.727. High-probability group (score > 81.82) may have potential benefits from ≥ 4 cycles consolidation chemotherapy (OR: 4.173, 95 % CI: 0.953-18.276, p = 0.058, pinteraction = 0.021). Conclusion: We identified and validated a model based on multicenter pre-treatment radiomics to predict ypT0-2 in cT3-4 LARC patients, which may facilitate individualised treatment decision-making for organ-preservation strategies and consolidation chemotherapy.

An updated overview of experimental and computational approaches to identify non-canonical DNA/RNA structures with emphasis on G-quadruplexes and R-loops.

Multiple types of non-canonical nucleic acid structures play essential roles in DNA recombination and replication, transcription, and genomic instability and have been associated with several human diseases. Thus, an increasing number of experimental and bioinformatics methods have been developed to identify these structures. To date, most reviews have focused on the features of non-canonical DNA/RNA structure formation, experimental approaches to mapping these structures, and the association of these structures with diseases. In addition, two reviews of computational algorithms for the prediction of non-canonical nucleic acid structures have been published. One of these reviews focused only on computational approaches for G4 detection until 2020. The other mainly summarized the computational tools for predicting cruciform, H-DNA and Z-DNA, in which the algorithms discussed were published before 2012. Since then, several experimental and computational methods have been developed. However, a systematic review including the conformation, sequencing mapping methods and computational prediction strategies for these structures has not yet been published. The purpose of this review is to provide an updated overview of conformation, current sequencing technologies and computational identification methods for non-canonical nucleic acid structures, as well as their strengths and weaknesses. We expect that this review will aid in understanding how these structures are characterised and how they contribute to related biological processes and diseases.

Pan-cancer analyses of synonymous mutations based on tissue-specific codon optimality.

Codon optimality has been demonstrated to be an important determinant of mRNA stability and expression levels in multiple model organisms and human cell lines. However, tissue-specific codon optimality has not been developed to investigate how codon optimality is usually perturbed by somatic synonymous mutations in human cancers. Here, we determined tissue-specific codon optimality in 29 human tissues based on mRNA expression data from the Genotype-Tissue Expression project. We found that optimal codons were associated with differentiation, whereas non-optimal codons were correlated with proliferation. Furthermore, codons biased toward differentiation displayed greater tissue specificity in codon optimality, and the tissue specificity of codon optimality was primarily present in amino acids with high degeneracy of the genetic code. By applying tissue-specific codon optimality to somatic synonymous mutations in 8532 tumor samples across 24 cancer types and to those in 416 normal cells across six human tissues, we found that synonymous mutations frequently increased optimal codons in tumor cells and cancer-related genes (e.g., genes involved in cell cycle). Furthermore, an elevated frequency of optimal codon gain was found to promote tumor cell proliferation in three cancer types characterized by DNA damage repair deficiency and could act as a prognostic biomarker for patients with triple-negative breast cancer. In summary, this study profiled tissue-specific codon optimality in human tissues, revealed alterations in codon optimality caused by synonymous mutations in human cancers, and highlighted the non-negligible role of optimal codon gain in tumorigenesis and therapeutics.

Transcriptomic signatures associated with autoimmune thyroiditis in papillary thyroid carcinoma and cancer immunotherapy-induced thyroid dysfunction.

Up to 20% of patients treated with anti-PD-1/PD-L1 inhibitors suffered from thyroid dysfunctions, yet the mediators associated with their occurrence remain unclear. The increasing coincidence of papillary thyroid carcinoma (PTC) with Hashimoto thyroiditis (HT) and the high vulnerability of thyroid to immunotherapy motivated us to discover the similarities and their underlying transcriptomic basis. Clinical characteristics analysis of 468 PTC patients from two independent cohorts and meta-analysis of 22,155 PTC patients unveiled a strong negative association between HT and recurrence in PTC patients. Transcriptome analysis of both cohorts showed PTC patients with HT were enriched in macrophages, CD8+ and CD4+ cytotoxic T cells, which was further validated by single-cell transcriptome analysis of 17,438 cells from PTC patients, and CD8+ T cells were correlated with disease-free survival of PTC patients. In both cohorts and single-cell dataset, elevated expression of PD-1-related genes was observed in the HT group, and CD3D appeared to be a target for enhancing the activation of CD8+ T cells. Correlation analysis of 3,318 thyroid adverse events from 39,123 patients across 24 tumor types and molecular signatures demonstrated similar signatures associated with autoimmune thyroiditis in PTC and thyroid immune-related adverse events (irAEs), and several multi-omics signatures, including signatures of CD8A and CD8+ T cells, showed positive associations with the odds ratio of thyroid irAEs. Our results unveil shared molecular signatures underlying thyroid dysfunction between patients receiving immunotherapies and PTC patients suffering from HT, which may shed light on managing the adverse events during cancer immunotherapy.

Integrative analysis prioritised oxytocin-related biomarkers associated with the aetiology of autism spectrum disorder.

BACKGROUND: Autism spectrum disorder (ASD) is a neurodevelopmental disorder with high phenotypic and genetic heterogeneity. The common variants of specific oxytocin-related genes (OTRGs), particularly OXTR, are associated with the aetiology of ASD. The contribution of rare genetic variations in OTRGs to ASD aetiology remains unclear. METHODS: We catalogued publicly available de novo mutations (DNMs) [from 6,511 patients with ASD and 3,391 controls], rare inherited variants (RIVs) [from 1,786 patients with ASD and 1,786 controls], and both de novo copy number variations (dnCNVs) and inherited CNVs (ihCNVs) [from 15,581 patients with ASD and 6,017 controls] in 963 curated OTRGs to explore their contribution to ASD pathology, respectively. Finally, a combined model was designed to prioritise the contribution of each gene to ASD aetiology by integrating DNMs and CNVs. FINDINGS: The rare genetic variations of OTRGs were significantly associated with ASD aetiology, in the order of dnCNVs > ihCNVs > DNMs. Furthermore, 172 OTRGs and their connected 286 ASD core genes were prioritised to positively contribute to ASD aetiology, including top-ranked MAPK3. Probands carrying rare disruptive variations in these genes were estimated to account for 10∼11% of all ASD probands. INTERPRETATION: Our findings suggest that rare disruptive variations in 172 OTRGs and their connected 286 ASD core genes are associated with ASD aetiology and may be potential biomarkers predicting the effects of oxytocin treatment. FUNDING: Guangdong Key Project, National Natural Science Foundation of China, Key Laboratory of Clinical Laboratory Diagnosis and Translational Research of Zhejiang Province.

MRI radiomics independent of clinical baseline characteristics and neoadjuvant treatment modalities predicts response to neoadjuvant therapy in rectal cancer.

BACKGROUND: To analyse the performance of multicentre pre-treatment MRI-based radiomics (MBR) signatures combined with clinical baseline characteristics and neoadjuvant treatment modalities to predict complete response to neoadjuvant (chemo)radiotherapy in locally advanced rectal cancer (LARC). METHODS: Baseline MRI and clinical characteristics with neoadjuvant treatment modalities at four centres were collected. Decision tree, support vector machine and five-fold cross-validation were applied for two non-imaging and three radiomics-based models' development and validation. RESULTS: We finally included 674 patients. Pre-treatment CEA, T stage, and histologic grade were selected to generate two non-imaging models: C model (clinical baseline characteristics alone) and CT model (clinical baseline characteristics combining neoadjuvant treatment modalities). The prediction performance of both non-imaging models were poor. The MBR signatures comprising 30 selected radiomics features, the MBR signatures combining clinical baseline characteristics (CMBR), and the CMBR incorporating neoadjuvant treatment modalities (CTMBR) all showed good discrimination with mean AUCs of 0.7835, 0.7871 and 0.7916 in validation sets, respectively. The three radiomics-based models had insignificant discrimination in performance. CONCLUSIONS: The performance of the radiomics-based models were superior to the non-imaging models. MBR signatures seemed to reflect LARC's true nature more accurately than clinical parameters and helped identify patients who can undergo organ preservation strategies.

Comprehensive evaluation of computational methods for predicting cancer driver genes.

Optimal methods could effectively improve the accuracy of predicting and identifying candidate driver genes. Various computational methods based on mutational frequency, network and function approaches have been developed to identify mutation driver genes in cancer genomes. However, a comprehensive evaluation of the performance levels of network-, function- and frequency-based methods is lacking. In the present study, we assessed and compared eight performance criteria for eight network-based, one function-based and three frequency-based algorithms using eight benchmark datasets. Under different conditions, the performance of approaches varied in terms of network, measurement and sample size. The frequency-based driverMAPS and network-based HotNet2 methods showed the best overall performance. Network-based algorithms using protein-protein interaction networks outperformed the function- and the frequency-based approaches. Precision, F1 score and Matthews correlation coefficient were low for most approaches. Thus, most of these algorithms require stringent cutoffs to correctly distinguish driver and non-driver genes. We constructed a website named Cancer Driver Catalog (http://159.226.67.237/sun/cancer_driver/), wherein we integrated the gene scores predicted by the foregoing software programs. This resource provides valuable guidance for cancer researchers and clinical oncologists prioritizing cancer driver gene candidates by using an optimal tool.