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Evidence on serum biomarkers as a non-invasive tool to detect colorectal adenoma (CRA) in the general population is quite promising. However, the sensitivity and specificity of these serum biomarkers in detecting disease are still questionable. This study aimed to systematically review the evidence on the diagnostic performance of serum biomarkers associated with CRA. Database searches on PubMed, Scopus, and WoS from January 2014 to December 2023 using PRISMA guidelines resulted in 4,380 citations, nine of which met inclusion criteria. The quality of these studies was assessed using the QUADOMICS tool. These studies reported on 77 individual/panel biomarkers which were further analysed to find associated altered pathways using MetaboAnlyst 5.0. Diagnostic accuracy analysis of these biomarkers was conducted by constructing a receiver operating characteristic (ROC) curve using their reported sensitivity and specificity. This review identified six potential serum metabolite biomarkers with 0.7

In this study of postmenopausal women in Malaysia, total adiposity was inversely associated with total BMD, while regional associations varied. No differences were detected across Malay, Chinese, and Indian ethnicities. Low BMD contributes substantially to morbidity and mortality, and increasing adiposity levels globally may be contributing to this., Purpose: To investigate associations of total and regional adiposity with bone mineral density (BMD) among a multi-ethnic cohort of postmenopausal women., Methods: Dual X-ray absorptiometry (DXA) imaging was undertaken for 1990 postmenopausal women without prior chronic diseases (30% Malay, 53% Chinese, and 17% Indian) from The Malaysian Cohort (TMC). The strength of the associations between standardized total and regional body fat percentages with total and regional BMD was examined using linear regression models adjusted for age, height, lean mass, ethnicity, education, and diabetes. Effect modification was assessed for ethnicity., Results: Women with a higher total body fat percentage were more likely to be Indian or Malay. Mean (SD) BMD for the whole-body total, lumbar spine, leg, and arm were 1.08 (0.11), 0.96 (0.15), 2.21 (0.22), and 1.36 (0.12) g/cm 2 , respectively. Total body and visceral fat percentage were inversely associated with total BMD (- 0.02 [95% CI - 0.03, - 0.01] and - 0.01 [- 0.02, - 0.006] g/cm 2 per 1 SD, respectively). In contrast, subcutaneous and gynoid fat percentages were positively associated with BMD (0.007 [0.002, 0.01] and 0.01 [0.006, 0.02] g/cm 2 , respectively). Total body fat percentage showed a weak positive association with lumbar BMD (0.01 [0.004, 0.02]) and inverse associations with leg (- 0.04 [- 0.06, - 0.03]) and arm (- 0.02 [- 0.03, - 0.02]) BMD in the highest four quintiles. There was no effect modification by ethnicity (p hetero  > 0.05)., Conclusion: Total adiposity was inversely associated with total BMD, although regional associations varied. There was no heterogeneity across ethnic groups suggesting adiposity may be a risk factor for low BMD across diverse populations., (© 2024. The Author(s).)

Triple-negative breast cancers (TNBCs) are a subset of breast cancers that have remained difficult to treat. A proportion of TNBCs arising in non-carriers of BRCA pathogenic variants have genomic features that are similar to BRCA carriers and may also benefit from PARP inhibitor treatment. Using genomic data from 129 TNBC samples from the Malaysian Breast Cancer (MyBrCa) cohort, we developed a gene expression-based machine learning classifier for homologous recombination deficiency (HRD) in TNBCs. The classifier identified samples with HRD mutational signature at an AUROC of 0.93 in MyBrCa validation datasets and 0.84 in TCGA TNBCs. Additionally, the classifier strongly segregated HRD-associated genomic features in TNBCs from TCGA, METABRIC, and ICGC. Thus, our gene expression classifier may identify triple-negative breast cancer patients with homologous recombination deficiency, suggesting an alternative method to identify individuals who may benefit from treatment with PARP inhibitors or platinum chemotherapy., (© 2024. The Author(s).)

The Integrative Cluster subtypes (IntClusts) provide a framework for the classification of breast cancer tumors into 10 distinct groups based on copy number and gene expression, each with unique biological drivers of disease and clinical prognoses. Gene expression data is often lacking, and accurate classification of samples into IntClusts with copy number data alone is essential. Current classification methods achieve low accuracy when gene expression data are absent, warranting the development of new approaches to IntClust classification. Copy number data from 1980 breast cancer samples from METABRIC was used to train multiclass XGBoost machine learning algorithms (CopyClust). A piecewise constant fit was applied to the average copy number profile of each IntClust and unique breakpoints across the 10 profiles were identified and converted into ~ 500 genomic regions used as features for CopyClust. These models consisted of two approaches: a 10-class model with the final IntClust label predicted by a single multiclass model and a 6-class model with binary reclassification in which four pairs of IntClusts were combined for initial multiclass classification. Performance was validated on the TCGA dataset, with copy number data generated from both SNP arrays and WES platforms. CopyClust achieved 81% and 79% overall accuracy with the TCGA SNP and WES datasets, respectively, a nine-percentage point or greater improvement in overall IntClust subtype classification accuracy. CopyClust achieves a significant improvement over current methods in classification accuracy of IntClust subtypes for samples without available gene expression data and is an easily implementable algorithm for IntClust classification of breast cancer samples with copy number data., (© 2024. The Author(s).)

B cells and T cells are important components of the adaptive immune system and mediate anticancer immunity. The T cell landscape in cancer is well characterized, but the contribution of B cells to anticancer immunosurveillance is less well explored. Here we show an integrative analysis of the B cell and T cell receptor repertoire from individuals with metastatic breast cancer and individuals with early breast cancer during neoadjuvant therapy. Using immune receptor, RNA and whole-exome sequencing, we show that both B cell and T cell responses seem to coevolve with the metastatic cancer genomes and mirror tumor mutational and neoantigen architecture. B cell clones associated with metastatic immunosurveillance and temporal persistence were more expanded and distinct from site-specific clones. B cell clonal immunosurveillance and temporal persistence are predictable from the clonal structure, with higher-centrality B cell antigen receptors more likely to be detected across multiple metastases or across time. This predictability was generalizable across other immune-mediated disorders. This work lays a foundation for prioritizing antibody sequences for therapeutic targeting in cancer., (© 2024. The Author(s).)

Breast cancer exhibits significant heterogeneity, manifesting in various subtypes that are critical in guiding treatment decisions. This study aimed to investigate the existence of distinct subtypes of breast cancer within the Asian population, by analysing the transcriptomic profiles of 934 breast cancer patients from a Malaysian cohort. Our findings reveal that the HR + /HER2- breast cancer samples display a distinct clustering pattern based on immune phenotypes, rather than conforming to the conventional luminal A-luminal B paradigm previously reported in breast cancers from women of European descent. This suggests that the activation of the immune system may play a more important role in Asian HR + /HER2- breast cancer than has been previously recognized. Analysis of somatic mutations by whole exome sequencing showed that counter-intuitively, the cluster of HR + /HER2- samples exhibiting higher immune scores was associated with lower tumour mutational burden, lower homologous recombination deficiency scores, and fewer copy number aberrations, implicating the involvement of non-canonical tumour immune pathways. Further investigations are warranted to determine the underlying mechanisms of these pathways, with the potential to develop innovative immunotherapeutic approaches tailored to this specific patient population., (© 2024. The Author(s).)

The effect of urea-loaded cellulose hydrogel, a controlled-release fertilizer (CRF) on growth and yield of upland rice were investigated in upland rice. As with the initial research, nitrogen (N) treatments were applied as CRF treatments; T2H (30 kg N ha -1 ), T3H (60 kg N ha -1 ), T4H (90 kg N ha -1 ), T5H (120 kg N ha -1 ) and recommended dose of fertilizer (RDF) at 120 kg N ha -1 RDF (T6U) in split application and T1 (0 N) as control. Results from this study indicated that applying CRF at the optimum N rate, T4H resulted in maximum grain yield, increasing by 71%. The analysis of yield components revealed that higher grain yield in T4H CRF was associated with an increase in panicle number and number of grains per panicle. Maximum grain N uptake of 0.25 g kg -1 was also observed in T4H CRF. In addition, T4H CRF recorded the highest harvest index (HI) and N harvest index (NHI) of 45.5% and 67.9%, respectively. Application of T4H CRF also recorded the highest N use efficiency (NUE) and N agronomic efficiency (NAE), 52.6% and 12.8 kg kg -1 , respectively. Observations show that CRF with only 75% N applied (T4H) in soil improved grain yield when compared to CRF with 100% N and 100% RDF in farmers' conventional split application. This suggested that CRF with a moderate N application might produce the highest potential yield and improved N efficiencies while enhancing crop production and further increase in N supply did not increase yield and N efficiencies. The results suggest that the application of T4H CRF for upland rice would enhance HI, N efficiencies and improve the yield of upland rice. Also, all growth parameters and yield were positively influenced by the application of CRF as a basal dose compared to split application of conventional urea fertilizers., (© 2023. The Author(s).)

The gut microbiota Parvimonas micra has been found to be enriched in gut mucosal tissues and fecal samples of colorectal cancer (CRC) patients compared with non-CRC controls. In the present study, we investigated the tumorigenic potential of P. micra and its regulatory pathways in CRC using HT-29, a low-grade CRC intestinal epithelial cell. For every P. micra-HT-29 interaction assay, HT-29 was co-cultured anaerobically with P. micra at an MOI of 100:1 (bacteria: cells) for 2 h. We found that P. micra increased HT-29 cell proliferation by 38.45% (P=0.008), with the highest wound healing rate at 24 h post-infection (P=0.02). In addition, inflammatory marker expression (IL-5, IL-8, CCL20, and CSF2) was also significantly induced. Shotgun proteomics profiling analysis revealed that P. micra affects the protein expression of HT-29 (157 up-regulated and 214 down-regulated proteins). Up-regulation of PSMB4 protein and its neighbouring subunits revealed association of the ubiquitin-proteasome pathway (UPP) in CRC carcinogenesis; whereas down-regulation of CUL1, YWHAH, and MCM3 signified cell cycle dysregulation. Moreover, 22 clinically relevant epithelial-mesenchymal transition (EMT)-markers were expressed in HT-29 infected with P. micra. Overall, the present study elucidated exacerbated oncogenic properties of P. micra in HT-29 via aberrant cell proliferation, enhanced wound healing, inflammation, up-regulation of UPPs, and activation of EMT pathways., (© 2023 The Author(s).)

Lupus nephritis is a severe manifestation of systemic lupus erythematosus (SLE). It is caused by immune dysregulation and kidney inflammation. In recent findings, gut microbiota potentially acts as primary mediators to enhance immune complex deposition, complement activation, and macrophage infiltration, and led to renal inflammation. Gut inflammation, known as leaky gut, allows pathogenic bacteria to enter the blood stream to form immune complexes which deposit on the kidney. Lymphocytes and macrophages induct a proinflammatory cytokine milieu that leads to kidney inflammation. Accumulating pieces of evidence from the field of gender bias, dietary habit, alcohol, smoking and antibiotic consumption were closely related to dysbiosis of gut microbiota in SLE. However, little is known about the causes of gut microbiota dysbiosis and the potential pathway that leads to lupus nephritis (LN) flare. In this review, we will bring into deeper insight for the potential link of gut microbiota on immune system with a particular focus on renal inflammation. Moreover, we also discuss the potential novel therapies that regulate gut composition to improve or complement the current treatment of LN.

Prediction model has been the focus of studies since the last century in the diagnosis and prognosis of various diseases. With the advancement in computational technology, machine learning (ML) has become the widely used tool to develop a prediction model. This review is to investigate the current development of prediction model for the risk of cardiovascular disease (CVD) among type 2 diabetes (T2DM) patients using machine learning. A systematic search on Scopus and Web of Science (WoS) was conducted to look for relevant articles based on the research question. The risk of bias (ROB) for all articles were assessed based on the Prediction model Risk of Bias Assessment Tool (PROBAST) statement. Neural network with 76.6% precision, 88.06% sensitivity, and area under the curve (AUC) of 0.91 was found to be the most reliable algorithm in developing prediction model for cardiovascular disease among type 2 diabetes patients. The overall concern of applicability of all included studies is low. While two out of 10 studies were shown to have high ROB, another studies ROB are unknown due to the lack of information. The adherence to reporting standards was conducted based on the Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD) standard where the overall score is 53.75%. It is highly recommended that future model development should adhere to the PROBAST and TRIPOD assessment to reduce the risk of bias and ensure its applicability in clinical settings. Potential lipid peroxidation marker is also recommended in future cardiovascular disease prediction model to improve overall model applicability., (© 2023. The Author(s).)

Food and diet are critical risk factors for colorectal cancer (CRC). Food environments (FEs) can contribute to disease risk, including CRC. This review investigated the link between FEs and CRC incidence and mortality risk. The systematic search of studies utilised three primary journal databases: PubMed, Scopus, and Web of Science. Retrieved citations were screened and the data were extracted from articles related to the FE-exposed populations who were at risk for CRC and death. We evaluated ecological studies and cohort studies with quality assessment and the Newcastle-Ottawa Quality Assessment Form for Cohort Studies, respectively. A descriptive synthesis of the included studies was performed. Out of 89 articles identified, eight were eligible for the final review. The included studies comprised six ecological studies and two cohort studies published from 2013 to 2021. Six articles were from the US, one was from Africa, and one was from Switzerland. All eight studies were of good quality. The significant finding was that CRC incidence was associated with the availability of specific foods such as red meat, meat, animal fats, energy from animal sources, and an unhealthy FE. Increased CRC mortality was linked with the availability of animal fat, red meat, alcoholic beverages, and calorie food availability, residence in food deserts, and lower FE index. There were a variety of associations between CRC and the FE. The availability of specific foods, unhealthy FE, and food desserts impact CRC incidence and mortality. Creating a healthy FE in the future will require focus and thorough planning.

Introduction: Translation of genome-wide association study (GWAS) findings into preventive approaches is challenged by the identification of the causal risk variants and the understanding of the biological mechanisms by which they act. We present using allelic expression (AE) ratios to perform quantitative case-control analysis as a novel approach to identify risk associations, causal regulatory variants, and target genes., Methods: Using the breast cancer (BC) risk locus 17q22 to validate this approach, we measured AE ratios in normal breast tissue samples from controls and cases, as well as from unmatched blood samples. Then we used in-silico and in-vitro analysis to map and functionally characterised candidate causal variants., Results: We found a significant shift in the AE patterns of STXBP4 (rs2628315) and COX11 (rs17817901) in the normal breast tissue of cases and healthy controls. Preferential expression of the G-rs2628315 and A-rs17817901 alleles, more often observed in cases, was associated with an increased risk for BC. Analysis of blood samples from cases and controls found a similar association. Furthermore, we identified two putative cis-regulatory variants - rs17817901 and rs8066588 - that affect a miRNA and a transcription factor binding site, respectively., Conclusion: We propose causal variants and target genes for the 17q22 BC risk locus and show that using AE ratios in case-control association studies is helpful in identifying risk and mapping causal variants., Competing Interests: Conflict of interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

PIK3CA mutations are the most common in breast cancer, particularly in the estrogen receptor-positive cohort, but the benefit of PI3K inhibitors has had limited success compared with approaches targeting other less common mutations. We found a frequent allelic expression imbalance between the missense mutant and wild-type PIK3CA alleles in breast tumors from the METABRIC (70.2%) and the TCGA (60.1%) projects. When considering the mechanisms controlling allelic expression, 27.7% and 11.8% of tumors showed imbalance due to regulatory variants in cis, in the two studies respectively. Furthermore, preferential expression of the mutant allele due to cis-regulatory variation is associated with poor prognosis in the METABRIC tumors (P = 0.031). Interestingly, ER-, PR-, and HER2+ tumors showed significant preferential expression of the mutated allele in both datasets. Our work provides compelling evidence to support the clinical utility of PIK3CA allelic expression in breast cancer in identifying patients of poorer prognosis, and those with low expression of the mutated allele, who will unlikely benefit from PI3K inhibitors. Furthermore, our work proposes a model of differential regulation of a critical cancer-promoting gene in breast cancer., (© 2022. The Author(s).)

The functions of the tumor microenvironment (TME) are orchestrated by precise spatial organization of specialized cells, yet little is known about the multicellular structures that form within the TME. Here we systematically mapped TME structures in situ using imaging mass cytometry and multitiered spatial analysis of 693 breast tumors linked to genomic and clinical data. We identified ten recurrent TME structures that varied by vascular content, stromal quiescence versus activation, and leukocyte composition. These TME structures had distinct enrichment patterns among breast cancer subtypes, and some were associated with genomic profiles indicative of immune escape. Regulatory and dysfunctional T cells co-occurred in large 'suppressed expansion' structures. These structures were characterized by high cellular diversity, proliferating cells and enrichment for BRCA1 and CASP8 mutations and predicted poor outcome in estrogen-receptor-positive disease. The multicellular structures revealed here link conserved spatial organization to local TME function and could improve patient stratification., (© 2022. The Author(s).)

Breast cancers are complex ecosystems of malignant cells and the tumour microenvironment 1 . The composition of these tumour ecosystems and interactions within them contribute to responses to cytotoxic therapy 2 . Efforts to build response predictors have not incorporated this knowledge. We collected clinical, digital pathology, genomic and transcriptomic profiles of pre-treatment biopsies of breast tumours from 168 patients treated with chemotherapy with or without HER2 (encoded by ERBB2)-targeted therapy before surgery. Pathology end points (complete response or residual disease) at surgery 3 were then correlated with multi-omic features in these diagnostic biopsies. Here we show that response to treatment is modulated by the pre-treated tumour ecosystem, and its multi-omics landscape can be integrated in predictive models using machine learning. The degree of residual disease following therapy is monotonically associated with pre-therapy features, including tumour mutational and copy number landscapes, tumour proliferation, immune infiltration and T cell dysfunction and exclusion. Combining these features into a multi-omic machine learning model predicted a pathological complete response in an external validation cohort (75 patients) with an area under the curve of 0.87. In conclusion, response to therapy is determined by the baseline characteristics of the totality of the tumour ecosystem captured through data integration and machine learning. This approach could be used to develop predictors for other cancers., (© 2021. The Author(s).)

Hyperpolarized 13 C-MRI is an emerging tool for probing tissue metabolism by measuring 13 C-label exchange between intravenously injected hyperpolarized [1- 13 C]pyruvate and endogenous tissue lactate. Here, we demonstrate that hyperpolarized 13 C-MRI can be used to detect early response to neoadjuvant therapy in breast cancer. Seven patients underwent multiparametric 1 H-MRI and hyperpolarized 13 C-MRI before and 7-11 days after commencing treatment. An increase in the lactate-to-pyruvate ratio of approximately 20% identified three patients who, following 5-6 cycles of treatment, showed pathological complete response. This ratio correlated with gene expression of the pyruvate transporter MCT1 and lactate dehydrogenase A ( LDHA ), the enzyme catalyzing label exchange between pyruvate and lactate. Analysis of approximately 2,000 breast tumors showed that overexpression of LDHA and the hypoxia marker CAIX was associated with reduced relapse-free and overall survival. Hyperpolarized 13 C-MRI represents a promising method for monitoring very early treatment response in breast cancer and has demonstrated prognostic potential. SIGNIFICANCE: Hyperpolarized carbon-13 MRI allows response assessment in patients with breast cancer after 7-11 days of neoadjuvant chemotherapy and outperformed state-of-the-art and research quantitative proton MRI techniques., (©2021 The Authors; Published by the American Association for Cancer Research.)

DNA methylation is aberrant in cancer, but the dynamics, regulatory role and clinical implications of such epigenetic changes are still poorly understood. Here, reduced representation bisulfite sequencing (RRBS) profiles of 1538 breast tumors and 244 normal breast tissues from the METABRIC cohort are reported, facilitating detailed analysis of DNA methylation within a rich context of genomic, transcriptional, and clinical data. Tumor methylation from immune and stromal signatures are deconvoluted leading to the discovery of a tumor replication-linked clock with genome-wide methylation loss in non-CpG island sites. Unexpectedly, methylation in most tumor CpG islands follows two replication-independent processes of gain (MG) or loss (ML) that we term epigenomic instability. Epigenomic instability is correlated with tumor grade and stage, TP53 mutations and poorer prognosis. After controlling for these global trans-acting trends, as well as for X-linked dosage compensation effects, cis-specific methylation and expression correlations are uncovered at hundreds of promoters and over a thousand distal elements. Some of these targeted known tumor suppressors and oncogenes. In conclusion, this study demonstrates that global epigenetic instability can erode cancer methylomes and expose them to localized methylation aberrations in-cis resulting in transcriptional changes seen in tumors., (© 2021. The Author(s).)

Cancer is a global health problem associated with genetics and unhealthy lifestyles. Increasingly, pathogenic infections have also been identified as contributors to human cancer initiation and progression. Most pathogens (bacteria, viruses, fungi, and parasites) associated with human cancers are categorized as Group I human carcinogens by the International Agency for Research on Cancer, IARC. These pathogens cause carcinogenesis via three known mechanisms: persistent infection that cause inflammation and DNA damage, initiation of oncogene expression, and immunosuppression activity of the host. In this review, we discuss the carcinogenesis mechanism of ten pathogens, their implications, and some future considerations for better management of the disease. The pathogens and cancers described are Helicobacter pylori (gastric cancer), Epstein-Barr virus (gastric cancer and lymphoma), Hepatitis B and C viruses (liver cancer), Aspergillus spp . (liver cancer), Opisthorchis viverrine (bile duct cancer), Clonorchis sinensis (bile duct cancer), Fusobacterium nucleatum (colorectal cancer), Schistosoma haematobium (bladder cancer); Human Papillomavirus (cervical cancer), and Kaposi's Sarcoma Herpes Virus (Kaposi's sarcoma).

The biology of breast cancer response to neoadjuvant therapy is underrepresented in the literature and provides a window-of-opportunity to explore the genomic and microenvironment modulation of tumours exposed to therapy. Here, we characterised the mutational, gene expression, pathway enrichment and tumour-infiltrating lymphocytes (TILs) dynamics across different timepoints of 35 HER2-negative primary breast cancer patients receiving neoadjuvant eribulin therapy (SOLTI-1007 NEOERIBULIN-NCT01669252). Whole-exome data (N = 88 samples) generated mutational profiles and candidate neoantigens and were analysed along with RNA-Nanostring 545-gene expression (N = 96 samples) and stromal TILs (N = 105 samples). Tumour mutation burden varied across patients at baseline but not across the sampling timepoints for each patient. Mutational signatures were not always conserved across tumours. There was a trend towards higher odds of response and less hazard to relapse when the percentage of subclonal mutations was low, suggesting that more homogenous tumours might have better responses to neoadjuvant therapy. Few driver mutations (5.1%) generated putative neoantigens. Mutation and neoantigen load were positively correlated (R 2  = 0.94, p = <0.001); neoantigen load was weakly correlated with stromal TILs (R 2  = 0.16, p = 0.02). An enrichment in pathways linked to immune infiltration and reduced programmed cell death expression were seen after 12 weeks of eribulin in good responders. VEGF was downregulated over time in the good responder group and FABP5, an inductor of epithelial mesenchymal transition (EMT), was upregulated in cases that recurred (p < 0.05). Mutational heterogeneity, subclonal architecture and the improvement of immune microenvironment along with remodelling of hypoxia and EMT may influence the response to neoadjuvant treatment.

A 30-kb deletion that eliminates the coding region of APOBEC3B (A3B) is >5 times more common in women of Asian descent compared to European descent. This polymorphism creates a chimera with the APOBEC3A (A3A) coding region and A3B 3'UTR, and it is associated with an increased risk for breast cancer in Asian women. Here, we explored the relationship between the A3B deletion polymorphism with tumour characteristics in Asian women. Using whole exome and whole transcriptome sequencing data of 527 breast tumours, we report that germline A3B deletion polymorphism leads to expression of the A3A-B hybrid isoform and increased APOBEC-associated somatic hypermutation. Hypermutated tumours, regardless of A3B germline status, were associated with the Her2 molecular subtype and PIK3CA mutations. Compared to nonhypermutated tumours, hypermutated tumours also had higher neoantigen burden, tumour heterogeneity and immune activation. Taken together, our results suggest that the germline A3B deletion polymorphism, via the A3A-B hybrid isoform, contributes to APOBEC mutagenesis in a significant proportion of Asian breast cancers. In addition, APOBEC somatic hypermutation, regardless of A3B background, may be an important clinical biomarker for Asian breast cancers., (© 2021 UICC.)

Rare protein-truncating variants (PTVs) in PALB2 confer increased risk to breast cancer, but relatively few studies have reported the characteristics of tumours with PALB2 PTVs. In this study, we describe molecular characteristics of tumours with either germline or somatic alterations in PALB2. DNA from fresh frozen tumour tissues and matched peripheral blood lymphocytes for 560 breast cancer patients was subjected for whole-exome sequencing (WES), and RNA from tumour tissues was subjected to RNA sequencing (RNA-seq). We found six cases with germline and three with somatic protein-truncating variants in PALB2. The characteristics of tumours in patients with PALB2 PTVs were similar to those with BRCA1 and BRCA2 PTVs, having significantly more somatic alterations, and a high proportion of the mutational signature and genomic scar scores characteristic of deficiencies in homologous recombination (HR), compared to tumours arising in non-carriers. Unlike tumours arising in patients with BRCA1 and BRCA2 PTVs, PALB2 tumours did not have high prevalence of TP53 somatic alterations or an enriched immune microenvironment. In summary, PALB2 tumours show the homologous recombination deficiencies characteristic of BRCA1 and BRCA2 tumours, and highlight the potential clinical relevance of PALB2 mutational status in guiding therapeutic choices.

The heterogeneity of breast cancer plays a major role in drug response and resistance and has been extensively characterized at the genomic level. Here, a single-cell breast cancer mass cytometry (BCMC) panel is optimized to identify cell phenotypes and their oncogenic signalling states in a biobank of patient-derived tumour xenograft (PDTX) models representing the diversity of human breast cancer. The BCMC panel identifies 13 cellular phenotypes (11 human and 2 murine), associated with both breast cancer subtypes and specific genomic features. Pre-treatment cellular phenotypic composition is a determinant of response to anticancer therapies. Single-cell profiling also reveals drug-induced cellular phenotypic dynamics, unravelling previously unnoticed intra-tumour response diversity. The comprehensive view of the landscapes of cellular phenotypic heterogeneity in PDTXs uncovered by the BCMC panel, which is mirrored in primary human tumours, has profound implications for understanding and predicting therapy response and resistance.

Autophagy is a conserved cellular process required to maintain homeostasis. The hallmark of autophagy is the formation of a phagophore that engulfs cytosolic materials for degradation and recycling to synthesize essential components. Basal autophagy is constitutively active under normal conditions and it could be further induced by physiological stimuli such as hypoxia, nutrient starvation, endoplasmic reticulum stress,energy depletion, hormonal stimulation and pharmacological treatment. In cancer, autophagy is highly context-specific depending on the cell type, tumour microenvironment, disease stage and external stimuli. Recently, the emerging role of autophagy as a double-edged sword in cancer has gained much attention. On one hand, autophagy suppresses malignant transformation by limiting the production of reactive oxygen species and DNA damage during tumour development. Subsequently, autophagy evolved to support the survival of cancer cells and promotes the tumourigenicity of cancer stem cells at established sites. Hence, autophagy is an attractive target for cancer therapeutics and researchers have been exploiting the use of autophagy modulators as adjuvant therapy. In this review, we present a summary of autophagy mechanism and controlling pathways, with emphasis on the dual-role of autophagy (double-edged sword) in cancer. This is followed by an overview of the autophagy modulation for cancer treatment and is concluded by a discussion on the current perspectives and future outlook of autophagy exploitation for precision medicine.

Dysbiosis of the gut microbiome has been associated with the pathogenesis of colorectal cancer (CRC). We profiled the microbiome of gut mucosal tissues from 18 CRC patients and 18 non-CRC controls of the UKM Medical Centre (UKMMC), Kuala Lumpur, Malaysia. The results were then validated using a species-specific quantitative PCR in 40 CRC and 20 non-CRC tissues samples from the UMBI-UKMMC Biobank. Parvimonas micra, Fusobacterium nucleatum, Peptostreptococcus stomatis and Akkermansia muciniphila were found to be over-represented in our CRC patients compared to non-CRC controls. These four bacteria markers distinguished CRC from controls (AUROC = 0.925) in our validation cohort. We identified bacteria species significantly associated (cut-off value of > 5 fold abundance) with various CRC demographics such as ethnicity, gender and CRC staging; however, due to small sample size of the discovery cohort, these results could not be further verified in our validation cohort. In summary, Parvimonas micra, Fusobacterium nucleatum, Peptostreptococcus stomatis and Akkermansia muciniphila were enriched in our local CRC patients. Nevertheless, the roles of these bacteria in CRC initiation and progression remains to be investigated.

Background: NRG1 gene fusions may be clinically actionable, since cancers carrying the fusion transcripts can be sensitive to tyrosine kinase inhibitors. The NRG1 gene encodes ligands for the HER2(ERBB2)-ERBB3 heterodimeric receptor tyrosine kinase, and the gene fusions are thought to lead to autocrine stimulation of the receptor. The NRG1 fusion expressed in the breast cancer cell line MDA-MB-175 serves as a model example of such fusions, showing the proposed autocrine loop and exceptional drug sensitivity. However, its structure has not been properly characterised, its oncogenic activity has not been fully explained, and there is limited data on such fusions in breast cancer., Methods: We analysed genomic rearrangements and transcripts of NRG1 in MDA-MB-175 and a panel of 571 breast cancers., Results: We found that the MDA-MB-175 fusion-originally reported as a DOC4(TENM4)-NRG1 fusion, lacking the cytoplasmic tail of NRG1-is in reality a double fusion, PPP6R3-TENM4-NRG1, producing multiple transcripts, some of which include the cytoplasmic tail. We hypothesise that many NRG1 fusions may be oncogenic not for lacking the cytoplasmic domain but because they do not encode NRG1's nuclear-localised form. The fusion in MDA-MB-175 is the result of a very complex genomic rearrangement, which we partially characterised, that creates additional expressed gene fusions, RSF1-TENM4, TPCN2-RSF1, and MRPL48-GAB2. We searched for NRG1 rearrangements in 571 breast cancers subjected to genome sequencing and transcriptome sequencing and found four cases (0.7%) with fusions, WRN-NRG1, FAM91A1-NRG1, ARHGEF39-NRG1, and ZNF704-NRG1, all splicing into NRG1 at the same exon as in MDA-MB-175. However, the WRN-NRG1 and ARHGEF39-NRG1 fusions were out of frame. We identified rearrangements of NRG1 in many more (8% of) cases that seemed more likely to inactivate than to create activating fusions, or whose outcome could not be predicted because they were complex, or both. This is not surprising because NRG1 can be pro-apoptotic and is inactivated in some breast cancers., Conclusions: Our results highlight the complexity of rearrangements of NRG1 in breast cancers and confirm that some do not activate but inactivate. Careful interpretation of NRG1 rearrangements will therefore be necessary for appropriate patient management.

Molecular profiling of breast cancer has enabled the development of more robust molecular prognostic signatures and therapeutic options for breast cancer patients. However, non-Caucasian populations remain understudied. Here, we present the mutational, transcriptional, and copy number profiles of 560 Malaysian breast tumours and a comparative analysis of breast cancers arising in Asian and Caucasian women. Compared to breast tumours in Caucasian women, we show an increased prevalence of HER2-enriched molecular subtypes and higher prevalence of TP53 somatic mutations in ER+ Asian breast tumours. We also observe elevated immune scores in Asian breast tumours, suggesting potential clinical response to immune checkpoint inhibitors. Whilst HER2-subtype and enriched immune score are associated with improved survival, presence of TP53 somatic mutations is associated with poorer survival in ER+ tumours. Taken together, these population differences unveil opportunities to improve the understanding of this disease and lay the foundation for precision medicine in different populations.

The burden of colorectal cancer (CRC) is increasing worldwide especially in developing countries. This phenomenon may be attributable to lifestyle, dietary and environmental risk factors. We aimed to determine the level of 25 trace elements, their interaction with environmental risk factors, and subsequently develop a risk prediction model for CRC (RPM CRC). For the discovery phase, we used a hospital-based case-control study (CRC and non-CRC patients) and in the validation phase we analysed pre-symptomatic samples of CRC patients from The Malaysian Cohort Biobank. Information on the environmental risk factors were obtained and level of 25 trace elements measured using the ICP-MS method. CRC patients had lower Zn and Se levels but higher Li, Be, Al, Co, Cu, As, Cd, Rb, Ba, Hg, Tl, and Pb levels compared to non-CRC patients. The positive interaction between red meat intake ≥ 50 g/day and Co ≥ 4.77 µg/L (AP 0.97; 95% CI 0.91, 1.03) doubled the risk of CRC. A panel of 24 trace elements can predict simultaneously and accurate of high, moderate, and low risk of CRC (accuracy 100%, AUC 1.00). This study provides a new input on possible roles for various trace elements in CRC as well as using a panel of trace elements as a screening approach to CRC.

Due to rapidly falling costs, whole genome sequencing (WGS) is becoming an essential tool in the surveillance of antimicrobial resistance (AMR) in Salmonella enterica. Although there have been many recent works evaluating the accuracy of WGS in predicting AMR from a large number of Salmonella isolates, little attention has been devoted to deciphering the underlying causes of disagreement between the WGS genotype and experimentally determined AMR phenotype. This study analyzed the genomes of six S. enterica isolates previously obtained from raw chicken which exhibited disagreements between WGS genotype and AMR phenotype. A total of five WGS false negative predictions toward ampicillin, amoxicillin/clavulanate, colistin, and fosfomycin resistance were presented in conjunction with their corresponding empirical phenotypic and/or genetic evidence of heteroresistance. A further case study highlighting the inherent limitations of WGS to detect the underlying genetic mechanisms of colistin heteroresistance was presented. These findings implicate heteroresistance as an underlying cause for false negative WGS-based AMR predictions in S. enterica and suggest that widespread use of WGS in the surveillance of AMR in food isolates might severely underestimate true resistance rates., Competing Interests: Declaration of competing interest The authors declare no conflict of interest., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Background: Low back pain (LBP) affects approximately 51% to 57% of hospital nurses and nurses' aides in Europe. New high-risk groups include home- and long-term-care nurses and physiotherapists. A number of European countries are experiencing a shortage of healthcare workers. Light therapy has been shown to be an effective treatment for various musculoskeletal disorders, including lateral epicondylitis, temporomandibular joint pain, carpal tunnel syndrome, and delayed-onset muscle soreness. A systematic review and meta-analysis demonstrated that low-level laser therapy is an effective method for relieving non-specific chronic low back pain (NSCLBP). However, the efficacy of light-emitting diode (LED) therapy for NSCLBP is disputed. This study aims to evaluate the effect of LED therapy on NSCLBP., Methods and Analysis: We conducted a prospective, double-blind, randomized placebo-controlled trial of 148 patients with NSCLBP. The patients were randomly assigned to 2 groups: intervention group, where patients received LED photobiomodulation therapy 3 times a week for 2 weeks, and the sham group, where patients had sham therapy 3 times a week for 2 weeks. Primary outcome measures included the visual analog scale for pain, lumbar active range of motion assessments, and chair-rising times. Secondary outcome measures included a multidimensional fatigue inventory, fear-avoidance beliefs questionnaire, and the Oswestry disability index. The outcome measures were assessed before therapy and 2weeks, 4 weeks, 8 weeks, 12 weeks, and 6 months after the first interventions were completed., Discussion: This study is a prospective, single-center, double-blind, randomized, controlled study. This study aims to research the efficacy of a 2-week LED program for NSCLBP working nurse. Our results will be useful for patients, working nurses, nurses' aides, and other healthcare workers with chronic low back pain., Trial Registration Number: NCT04424823.

As the catalog of oncogenic driver mutations is expanding, it becomes clear that alterations in a given gene might have different functions and should not be lumped into one class. The transcription factor GATA3 is a paradigm of this. We investigated the functions of the most common GATA3 mutation (X308&#95;Splice) and five additional mutations, which converge into a neoprotein that we called "neoGATA3," associated with excellent prognosis in patients. Analysis of available molecular data from >3000 breast cancer patients revealed a dysregulation of the ER-dependent transcriptional response in tumors carrying neoGATA3-generating mutations. Mechanistic studies in vitro showed that neoGATA3 interferes with the transcriptional programs controlled by estrogen and progesterone receptors, without fully abrogating them. ChIP-Seq analysis indicated that ER binding is reduced in neoGATA3-expressing cells, especially at distal regions, suggesting that neoGATA3 interferes with the fine tuning of ER-dependent gene expression. This has opposite outputs in distinct hormonal context, having pro- or anti-proliferative effects, depending on the estrogen/progesterone ratio. Our data call for functional analyses of putative cancer drivers to guide clinical application.

TP53 gene mutations are very common in human cancer. While such mutations abrogate the tumor suppressive activities of the wild-type (wt) p53 protein, some of them also endow the mutant (mut) protein with oncogenic gain of function (GOF), facilitating cancer progression. Yet, p53 may acquire altered functionality even without being mutated; in particular, experiments with cultured cells revealed that wtp53 can be rewired to adopt mut-like features in response to growth factors or cancer-mimicking genetic manipulations. To assess whether such rewiring also occurs in human tumors, we interrogated gene expression profiles and pathway deregulation patterns in the METABRIC breast cancer (BC) dataset as a function of TP53 gene mutation status. Harnessing the power of machine learning, we optimized a gene expression classifier for ER+Her2- patients that distinguishes tumors carrying TP53 mutations from those retaining wt TP53. Interestingly, a small subset of wt TP53 tumors displayed gene expression and pathway deregulation patterns markedly similar to those of TP53-mutated tumors. Moreover, similar to TP53-mutated tumors, these 'pseudomutant' cases displayed a signature for enhanced proliferation and had worse prognosis than typical wtp53 tumors. Notably, these tumors revealed upregulation of genes which, in BC cell lines, were reported to be positively regulated by p53 GOF mutants. Thus, such tumors may benefit from mut p53-associated activities without having to accrue TP53 mutations., (© 2020 The Authors. Published by FEBS Press and John Wiley & Sons Ltd.)

Global insights into cellular organization and genome function require comprehensive understanding of the interactome networks that mediate genotype-phenotype relationships 1,2 . Here we present a human 'all-by-all' reference interactome map of human binary protein interactions, or 'HuRI'. With approximately 53,000 protein-protein interactions, HuRI has approximately four times as many such interactions as there are high-quality curated interactions from small-scale studies. The integration of HuRI with genome 3 , transcriptome 4 and proteome 5 data enables cellular function to be studied within most physiological or pathological cellular contexts. We demonstrate the utility of HuRI in identifying the specific subcellular roles of protein-protein interactions. Inferred tissue-specific networks reveal general principles for the formation of cellular context-specific functions and elucidate potential molecular mechanisms that might underlie tissue-specific phenotypes of Mendelian diseases. HuRI is a systematic proteome-wide reference that links genomic variation to phenotypic outcomes.

Genomic alterations shape cell phenotypes and the structure of tumor ecosystems in poorly defined ways. To investigate these relationships, we used imaging mass cytometry to quantify the expression of 37 proteins with subcellular spatial resolution in 483 tumors from the METABRIC cohort. Single-cell analysis revealed cell phenotypes spanning epithelial, stromal and immune types. Distinct combinations of cell phenotypes and cell-cell interactions were associated with genomic subtypes of breast cancer. Epithelial luminal cell phenotypes separated into those predominantly impacted by mutations and those affected by copy number aberrations. Several features of tumor ecosystems, including cellular neighborhoods, were linked to prognosis, illustrating their clinical relevance. In summary, systematic analysis of single-cell phenotypic and spatial correlates of genomic alterations in cancer revealed how genomes shape both the composition and architecture of breast tumor ecosystems and will enable greater understanding of the phenotypic impact of genomic alterations., (© 2020. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Our purpose is to investigate the feasibility of imaging tumor metabolism in breast cancer patients using 13 C magnetic resonance spectroscopic imaging (MRSI) of hyperpolarized 13 C label exchange between injected [1- 13 C]pyruvate and the endogenous tumor lactate pool. Treatment-naïve breast cancer patients were recruited: four triple-negative grade 3 cancers; two invasive ductal carcinomas that were estrogen and progesterone receptor-positive (ER/PR+) and HER2/neu-negative (HER2-), one grade 2 and one grade 3; and one grade 2 ER/PR+ HER2- invasive lobular carcinoma (ILC). Dynamic 13 C MRSI was performed following injection of hyperpolarized [1- 13 C]pyruvate. Expression of lactate dehydrogenase A (LDHA), which catalyzes 13 C label exchange between pyruvate and lactate, hypoxia-inducible factor-1 (HIF1α), and the monocarboxylate transporters MCT1 and MCT4 were quantified using immunohistochemistry and RNA sequencing. We have demonstrated the feasibility and safety of hyperpolarized 13 C MRI in early breast cancer. Both intertumoral and intratumoral heterogeneity of the hyperpolarized pyruvate and lactate signals were observed. The lactate-to-pyruvate signal ratio (LAC/PYR) ranged from 0.021 to 0.473 across the tumor subtypes (mean ± SD: 0.145 ± 0.164), and a lactate signal was observed in all of the grade 3 tumors. The LAC/PYR was significantly correlated with tumor volume ( R = 0.903, P = 0.005) and MCT 1 ( R = 0.85, P = 0.032) and HIF1α expression ( R = 0.83, P = 0.043). Imaging of hyperpolarized [1- 13 C]pyruvate metabolism in breast cancer is feasible and demonstrated significant intertumoral and intratumoral metabolic heterogeneity, where lactate labeling correlated with MCT1 expression and hypoxia., Competing Interests: Competing interest statement: A research agreement is in place between GE Healthcare and K.M.B. and F.A.G., (Copyright © 2020 the Author(s). Published by PNAS.)

Identifying the underlying genetic drivers of the heritability of breast cancer prognosis remains elusive. We adapt a network-based approach to handle underpowered complex datasets to provide new insights into the potential function of germline variants in breast cancer prognosis. This network-based analysis studies ~7.3 million variants in 84,457 breast cancer patients in relation to breast cancer survival and confirms the results on 12,381 independent patients. Aggregating the prognostic effects of genetic variants across multiple genes, we identify four gene modules associated with survival in estrogen receptor (ER)-negative and one in ER-positive disease. The modules show biological enrichment for cancer-related processes such as G-alpha signaling, circadian clock, angiogenesis, and Rho-GTPases in apoptosis.

Purpose: Invasive lobular carcinoma (ILC) is a subtype of breast cancer accounting for 10% of breast tumors. The majority of patients are treated with endocrine therapy; however, endocrine resistance is common in estrogen receptor-positive breast cancer and new therapeutic strategies are needed. Bromodomain and extraterminal inhibitors (BETi) are effective in diverse types of breast cancer but they have not yet been assessed in ILC., Experimental Design: We assessed whether targeting the BET proteins with JQ1 could serve as an effective therapeutic strategy in ILC in both 2D and 3D models. We used dynamic BH3 profiling and RNA-sequencing (RNA-seq) to identify transcriptional reprograming enabling resistance to JQ1-induced apoptosis. As part of the RATHER study, we obtained copy-number alterations and RNA-seq on 61 ILC patient samples., Results: Certain ILC cell lines were sensitive to JQ1, while others were intrinsically resistant to JQ1-induced apoptosis. JQ1 treatment led to an enhanced dependence on antiapoptotic proteins and a transcriptional rewiring inducing fibroblast growth factor receptor 1 (FGFR1). This increase in FGFR1 was also evident in invasive ductal carcinoma (IDC) cell lines. The combination of JQ1 and FGFR1 inhibitors was highly effective at inhibiting growth in both 2D and 3D models of ILC and IDC. Interestingly, we found in the RATHER cohort of 61 ILC patients that 20% had FGFR1 amplification and we showed that high BRD3 mRNA expression was associated with poor survival specifically in ILC., Conclusions: We provide evidence that BETi either alone or in combination with FGFR1 inhibitors or BH3 mimetics may be a useful therapeutic strategy for recurrent ILC patients., (©2019 American Association for Cancer Research.)

Introduction: In recent years, trace elements have gained importance as biomarkers in many chronic diseases. Unfortunately, the requirement for sample volume increases with the extent of investigation either for diagnosis or elucidating the mechanism of the disease. Here, we describe the method development and validation for simultaneous determination of 25 trace elements (lithium [Li], beryllium [Be], magnesium [Mg], aluminium [Al], vanadium [V], chromium [Cr], manganese [Mn], iron [Fe], cobalt [Co], nickel [Ni], copper [Cu], zinc [Zn], gallium [Ga], arsenic [As], selenium [Se], rubidium [Rb], strontium [Sr], silver [Ag], cadmium [Cd], caesium [Cs], barium [Ba], mercury [Hg], thallium [Tl], lead [Pb], uranium [U]) using only 20 μL of human serum., Methods: Serum samples were digested with nitric acid and hydrochloric acid (ratio 1:1, v/v) and analysed by inductively coupled plasma-mass spectrometry (ICP-MS). Seronorm®, a human-derived serum control material was used as quality control samples., Results: The coefficient of variations for both intra- and inter-day precisions were consistently <15% for all elements. The validated method was later tested on 30 human serum samples to evaluate its applicability., Conclusion: We have successfully developed and validated a precise and accurate analytical method for determining 25 trace elements requiring very low volume of human serum., Competing Interests: The authors declare that they have no conflicts of interest related the contents of this article., (© 2019 The Authors.)

Longitudinal analysis of circulating tumor DNA (ctDNA) has shown promise for monitoring treatment response. However, most current methods lack adequate sensitivity for residual disease detection during or after completion of treatment in patients with nonmetastatic cancer. To address this gap and to improve sensitivity for minute quantities of residual tumor DNA in plasma, we have developed targeted digital sequencing (TARDIS) for multiplexed analysis of patient-specific cancer mutations. In reference samples, by simultaneously analyzing 8 to 16 known mutations, TARDIS achieved 91 and 53% sensitivity at mutant allele fractions (AFs) of 3 in 10 4 and 3 in 10 5 , respectively, with 96% specificity, using input DNA equivalent to a single tube of blood. We successfully analyzed up to 115 mutations per patient in 80 plasma samples from 33 women with stage I to III breast cancer. Before treatment, TARDIS detected ctDNA in all patients with 0.11% median AF. After completion of neoadjuvant therapy, ctDNA concentrations were lower in patients who achieved pathological complete response (pathCR) compared to patients with residual disease (median AFs, 0.003 and 0.017%, respectively, P = 0.0057, AUC = 0.83). In addition, patients with pathCR showed a larger decrease in ctDNA concentrations during neoadjuvant therapy. These results demonstrate high accuracy for assessment of molecular response and residual disease during neoadjuvant therapy using ctDNA analysis. TARDIS has achieved up to 100-fold improvement beyond the current limit of ctDNA detection using clinically relevant blood volumes, demonstrating that personalized ctDNA tracking could enable individualized clinical management of patients with cancer treated with curative intent., (Copyright © 2019 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)