Controlling the confounding effect of metabolic gene expression to identify actual metabolite targets in microsatellite instability cancers.

BACKGROUND: The metabolome is the best representation of cancer phenotypes. Gene expression can be considered a confounding covariate affecting metabolite levels. Data integration across metabolomics and genomics to establish the biological relevance of cancer metabolism is challenging. This study aimed to eliminate the confounding effect of metabolic gene expression to reflect actual metabolite levels in microsatellite instability (MSI) cancers. METHODS: In this study, we propose a new strategy using covariate-adjusted tensor classification in high dimensions (CATCH) models to integrate metabolite and metabolic gene expression data to classify MSI and microsatellite stability (MSS) cancers. We used datasets from the Cancer Cell Line Encyclopedia (CCLE) phase II project and treated metabolomic data as tensor predictors and data on gene expression of metabolic enzymes as confounding covariates. RESULTS: The CATCH model performed well, with high accuracy (0.82), sensitivity (0.66), specificity (0.88), precision (0.65), and F1 score (0.65). Seven metabolite features adjusted for metabolic gene expression, namely, 3-phosphoglycerate, 6-phosphogluconate, cholesterol ester, lysophosphatidylethanolamine (LPE), phosphatidylcholine, reduced glutathione, and sarcosine, were found in MSI cancers. Only one metabolite, Hippurate, was present in MSS cancers. The gene expression of phosphofructokinase 1 (PFKP), which is involved in the glycolytic pathway, was related to 3-phosphoglycerate. ALDH4A1 and GPT2 were associated with sarcosine. LPE was associated with the expression of CHPT1, which is involved in lipid metabolism. The glycolysis, nucleotide, glutamate, and lipid metabolic pathways were enriched in MSI cancers. CONCLUSIONS: We propose an effective CATCH model for predicting MSI cancer status. By controlling the confounding effect of metabolic gene expression, we identified cancer metabolic biomarkers and therapeutic targets. In addition, we provided the possible biology and genetics of MSI cancer metabolism.

Dual role of sprouty2 as an inhibitor of RAS/ERK-driven proliferation and a promoter of cancer invasion in KRAS wild-type colorectal cancer.

Sprouty2 (SPRY2) is known to inhibit the RAS/MAPK/ERK pathway, and is a potential study target for cancer. The effect of SPRY2 in colorectal cancer (CRC) and whether it is influenced by KRAS mutation are not known. We manipulated SPRY2 gene expression and used an activating KRAS-mutant plasmid to determine its effect on CRC cell function in vitro and/or in vivo. We performed SPRY2 immunohistochemical staining in 143 CRC specimens and analyzed the staining results with various clinicopathological characteristics in relation to KRAS mutation status. SPRY2 knockdown in Caco-2 cells carrying the wild-type (WT) KRAS gene upregulated phosphorylated ERK (p-ERK) levels and increased cell proliferation in vitro, but inhibited cell invasion. However, SPRY2 knockdown in SW480 cells (activating KRAS mutant) or Caco-2 cells transfected with KRAS-mutant plasmid did not significantly alter p-ERK levels, cell proliferation, or invasion. The xenografts of SPRY2-knockdown Caco-2 cells were larger with less deep muscle invasion than those of control cells. The clinical cohort study revealed a positive association of SPRY2 protein expression with pT status, lymphovascular invasion, and perineural invasion in KRAS-WT CRCs. However, the associations were not observed in KRAS-mutant CRCs. Interestingly, high SPRY2 expression was related to shorter cancer-specific survival in both KRAS-WT and KRAS-mutant CRC patients. Our study demonstrated the dual role of SPRY2 as an inhibitor of RAS/ERK-driven proliferation and as a promoter of cancer invasion in KRAS-WT CRC. SPRY2 may promote the invasion and progression of KRAS-WT CRC, and might also enhance KRAS-mutant CRC progression through pathways other than invasion.

Precise uncertain significance prediction using latent space matrix factorization models: genomics variant and heterogeneous clinical data-driven approaches.

Several studies to date have proposed different types of interpreters for measuring the degree of pathogenicity of variants. However, in predicting the disease type and disease-gene associations, scholars face two essential challenges, namely the vast number of existing variants and the existence of variants which are recognized as variant of uncertain significance (VUS). To tackle these challenges, we propose algorithms to assign a significance to each gene rather than each variant, describing its degree of pathogenicity. Since the interpreters identified most of the variants as VUS, most of the gene scores were identified as uncertain significance. To predict the uncertain significance scores, we design two matrix factorization-based models: the common latent space model uses genomics variant data as well as heterogeneous clinical data, while the single-matrix factorization model can be used when heterogeneous clinical data are unavailable. We have managed to show that the models successfully predict the uncertain significance scores with low error and high accuracy. Moreover, to evaluate the effectiveness of our novel input features, we train five different multi-label classifiers including a feedforward neural network with the same feature set and show they all achieve high accuracy as the main impact of our approach comes from the features. Availability: The source code is freely available at https://github.com/sabdollahi/CoLaSpSMFM.

A novel deep learning-based algorithm combining histopathological features with tissue areas to predict colorectal cancer survival from whole-slide images.

BACKGROUND: Many methodologies for selecting histopathological images, such as sample image patches or segment histology from regions of interest (ROIs) or whole-slide images (WSIs), have been utilized to develop survival models. With gigapixel WSIs exhibiting diverse histological appearances, obtaining clinically prognostic and explainable features remains challenging. Therefore, we propose a novel deep learning-based algorithm combining tissue areas with histopathological features to predict cancer survival. METHODS: The Cancer Genome Atlas Colon Adenocarcinoma (TCGA-COAD) dataset was used in this investigation. A deep convolutional survival model (DeepConvSurv) extracted histopathological information from the image patches of nine different tissue types, including tumors, lymphocytes, stroma, and mucus. The tissue map of the WSIs was segmented using image processing techniques that involved localizing and quantifying the tissue region. Six survival models with the concordance index (C-index) were used as the evaluation metrics. RESULTS: We extracted 128 histopathological features from four histological types and five tissue area features from WSIs to predict colorectal cancer survival. Our method performed better in six distinct survival models than the Whole Slide Histopathological Images Survival Analysis framework (WSISA), which adaptively sampled patches using K-means from WSIs. The best performance using histopathological features was 0.679 using LASSO-Cox. Compared to histopathological features alone, tissue area features increased the C-index by 2.5%. Based on histopathological features and tissue area features, our approach achieved performance of 0.704 with RIDGE-Cox. CONCLUSIONS: A deep learning-based algorithm combining histopathological features with tissue area proved clinically relevant and effective for predicting cancer survival.

Lidocaine transdermal patches reduced pain intensity in neuropathic cancer patients already receiving opioid treatment.

BACKGROUND: Limited efficacy has been observed when using opioids to treat neuropathic pain. Lidocaine patches reduce neuropathic pain in postherpetic neuralgia, but their benefits for cancer-related neuropathic pain remain unclear. This study aimed to investigate a treatment for cancer-related neuropathic pain. METHODS: We conducted a prospective, open-label, single-arm study to assess the efficacy and safety of lidocaine transdermal patches in patients experiencing localized, superficial, neuropathic cancer pain. Terminal cancer patients already receiving opioid treatment participated in the 3-day study. The primary endpoint was pain intensity evaluated by the numerical rating scale (NRS). The secondary endpoints were the pain relief score and the quality of analgesic treatment. RESULTS: The results showed a significant difference in the median NRS over 3 days (Kruskal-Wallis test, p < 0.0001). The median NRS pain intensity from Day 1 to Day 3 was 4.0 with 95% C.I. (3.3, 5.0), 3.0 (2.5, 3.5), and 2.6 (2.0, 3.0), respectively. The difference between the median NRS pain intensities of any 2 days was significant (Wilcoxon signed-rank test, p < 0.0001). The generalized estimating equation (GEE) estimation model showed significant differences between the NRS pain intensities on any 2 days. There was no significant difference in the pain relief score or the quality of analgesic treatment. CONCLUSIONS: In this study, the 5% lidocaine transdermal patch reduced the NRS pain intensity in neuropathic cancer patients already receiving opioid treatment. Treatment of localized and superficial neuropathic pain caused by cancer was well tolerated and effective.

CHK2 activation contributes to the development of oxaliplatin resistance in colorectal cancer.

BACKGROUND: Colorectal cancer (CRC), the most common cancer type, causes high morbidity and mortality. Patients who develop drug resistance to oxaliplatin-based regimens have short overall survival. Thus, identifying molecules involved in the development of oxaliplatin resistance is critical for designing therapeutic strategies. METHODS: A proteomic screen was performed to reveal altered protein kinase phosphorylation in oxaliplatin-resistant (OR) CRC tumour spheroids. The function of CHK2 was characterised using several biochemical techniques and evident using in vitro cell and in vivo tumour models. RESULTS: We revealed that the level of phospho-CHK2(Thr68) was elevated in OR CRC cells and in ~30% of tumour samples from patients with OR CRC. We demonstrated that oxaliplatin activated several phosphatidylinositol 3-kinase-related kinases (PIKKs) and CHK2 downstream effectors and enhanced CHK2/PARP1 interaction to facilitate DNA repair. A phosphorylation mimicking CHK2 mutant, CHK2T68D, but not a kinase-dead CHK2 mutant, CHK2D347A, promoted DNA repair, the CHK2/PARP1 interaction, and cell growth in the presence of oxaliplatin. Finally, we showed that a CHK2 inhibitor, BML-277, reduced protein poly(ADP-ribosyl)ation (PARylation), FANCD2 monoubiquitination, homologous recombination and OR CRC cell growth in vitro and in vivo. CONCLUSION: Our findings suggest that CHK2 activity is critical for modulating oxaliplatin response and that CHK2 is a potential therapeutic target for OR CRC.

Impact of BRCA mutation on the survival and risk of contralateral breast cancer in Asian breast cancer patients.

PURPOSE: Breast cancer is increasing around the globe, including Asia. We aimed to examine the survival and risk of contralateral breast cancer (CBC) in Asian breast cancer patients with BRCA mutations. METHODS: A total of 128 breast cancer patients with germline BRCA mutations and 4,754 control breast cancer patients were enrolled. Data on clinical-pathologic characteristics, survival, and CBC were collected from the medical record. The rates of survival and CBC were estimated by Kaplan-Meier method. RESULTS: The mean age of onset in BRCA mutation carriers was significantly younger than control patients (BRCA vs. Non-BRCA: 43.9 vs. 53.2 years old). BRCA mutation carriers had a higher proportion of triple-negative breast cancer (TNBC) (52%) than control patients (12%, p < 0.001). The risk of CBC was significantly higher in BRCA mutation patients than in control cases (hazard ratio (HR) = 3.95, 95% CI 2.71-5.75); when stratified by genotype, the HRs (95%CI) were 4.84 (3.00-7.82) for BRCA1 and 3.13 (1.78-5.49) for BRCA2 carriers, respectively. Moreover, BRCA1 mutation patients with triple-negative breast cancer (TNBC) as their first breast cancer had the highest risk of CBC (HR = 5.55, 95% CI 3.29-9.34). However, we did not observe any differences in relapse-free survival and overall survival between mutation carriers and control patients. CONCLUSION: Our study suggest that BRCA patients had a significantly higher risk of developing CBC, particularly for BRCA1 mutation carriers with TNBC as the first breast cancer.

Comprehensive assessments of germline deletion structural variants reveal the association between prognostic MUC4 and CEP72 deletions and immune response gene expression in colorectal cancer patients.

BACKGROUND: Functional disruptions by large germline genomic structural variants in susceptible genes are known risks for cancer. We used deletion structural variants (DSVs) generated from germline whole-genome sequencing (WGS) and DSV immune-related association tumor microenvironment (TME) to predict cancer risk and prognosis. METHODS: We investigated the contribution of germline DSVs to cancer susceptibility and prognosis by silicon and causal inference models. DSVs in germline WGS data were generated from the blood samples of 192 cancer and 499 non-cancer subjects. Clinical information, including family cancer history (FCH), was obtained from the National Cheng Kung University Hospital and Taiwan Biobank. Ninety-nine colorectal cancer (CRC) patients had immune response gene expression data. We used joint calling tools and an attention-weighted model to build the cancer risk predictive model and identify DSVs in familial cancer. The survival support vector machine (survival-SVM) was used to select prognostic DSVs. RESULTS: We identified 671 DSVs that could predict cancer risk. The area under the curve (AUC) of the receiver operating characteristic curve (ROC) of the attention-weighted model was 0.71. The 3 most frequent DSV genes observed in cancer patients were identified as ADCY9, AURKAPS1, and RAB3GAP2 (p < 0.05). The DSVs in SGSM2 and LHFPL3 were relevant to colorectal cancer. We found a higher incidence of FCH in cancer patients than in non-cancer subjects (p < 0.05). SMYD3 and NKD2DSV genes were associated with cancer patients with FCH (p < 0.05). We identified 65 immune-associated DSV markers for assessing cancer prognosis (p < 0.05). The functional protein of MUC4 DSV gene interacted with MAGE1 expression, according to the STRING database. The causal inference model showed that deleting the CEP72 DSV gene affect the recurrence-free survival (RFS) of IFIT1 expression. CONCLUSIONS: We established an explainable attention-weighted model for cancer risk prediction and used the survival-SVM for prognostic stratification by using germline DSVs and immune gene expression datasets. Comprehensive assessments of germline DSVs can predict the cancer risk and clinical outcome of colon cancer patients.

A case of acquired hemophilia A and bullous pemphigoid following SARS-CoV-2 mRNA vaccination.

Acquired hemophilia is a rare disease resulting from autoantibodies against endogenous factor VIII (FVIII), which associates with bleeding and a high mortality rate. The pathophysiology is still unclear. Recent studies suggest genetic and environmental factors trigger the breakdown of immune tolerance. We report a 77-year-old Taiwanese man presented with multiple ecchymoses and some hemorrhagic blisters three weeks after SARS-CoV-2 mRNA (Moderna) vaccination. Isolated activated partial thromboplastin time (aPTT) prolongation was found. Acquired hemophilia A (AHA) was confirmed by low factor VIII (FVIII) activity and high titer of FVIII inhibitor. The pathohistology of skin biopsy further supported the concomitant diagnosis of bullous pemphigoid. To date, 6 cases of acquired hemophilia A following SARS-CoV-2 mRNA vaccination were reported worldwide. We reviewed and summarized the characteristics of these cases. We also discussed the rare finding of concomitant acquired hemophilia A and bullous pemphigoid. Bullous pemphigoid results from autoantibody against epithelial basement membrane zone of skin. In this article, we proposed possibility of SARS-CoV-2 mRNA vaccine associated autoimmunity against FVIII and epithelial basement membrane zone.

PD-L1 Expression in High-Risk Early-Stage Colorectal Cancer-Its Clinical and Biological Significance in Immune Microenvironment.

Programmed death-ligand 1 (PD-L1) is an immune checkpoint molecule that can regulate immune responses in the tumor microenvironment (TME); however, the clinical applications of PD-L1 in early-stage colorectal cancer (CRC) remain unclear. In this study, we aimed to investigate the relationship between PD-L1 expression and survival outcome and explore its relevant immune responses in CRC. PD-L1 expression was evaluated by immunohistochemical staining to determine the tumor proportion score and combined positive score (CPS) in a Taiwanese CRC cohort. The oncomine immune response research assay was conducted for immune gene expression analyses. CRC datasets from the TCGA database were reappraised for PD-L1-associated gene enrichment analyses using GSEA. The high expression of PD-L1 (CPS ≥ 5) was associated with longer recurrence-free survival (p = 0.031) and was an independent prognostic factor as revealed by multivariate analysis. High PD-L1 expression was related to six immune-related gene signatures, and CXCL9 is the most significant overexpressed gene in differential analyses. High CXCL9 expression correlated with increased infiltration levels of immune cells in the TME, including CD8+ T lymphocytes and M1 macrophages. These findings suggest that high PD-L1 expression is a prognostic factor of early-stage CRC, and CXCL9 may play a key role in regulating PD-L1 expression.

Sequential and co-occurring DNA damage response genetic mutations impact survival in stage III colorectal cancer patients receiving adjuvant oxaliplatin-based chemotherapy.

BACKGROUND: Certain sequences of genomic mutations can lead to cancer formation and affect treatment outcomes and drug resistance. We constructed a cancer evolutionary tree using bulk-targeted deep sequencing to explore the impact of sequential and co-occurring somatic mutations on patients with stage III colorectal cancer (CRC). METHODS: A total of 108 stage III CRC patients from National Cheng Kung University Hospital (NCKUH) were recruited for this study between Jan. 2014 and Jan. 2019. Clinical information and tumor-targeted deep sequencing data were collected. Phylogenetic trees were reconstructed for evolutionary trajectories. We used a machine learning model for survival analysis. RESULTS: Six sequential somatic mutations stratified patients into seven subgroups based on survival. Patients carrying sequential germline followed by DNA damage response-related ATM or BRCA2 somatic mutations or non-TP53, APC somatic mutations had a better outcome than those without such mutations. The 4-year recurrence-free survival (RFS) probability was 88% in the low-risk group (G1) and 46% in the high-risk group (G2) (log-rank p-value 2e-05). The predictive efficacy by the area under the curve (AUC) was 0.73, 0.7, 0.797, and 0.88 at 2, 4, 6, and 8 years, respectively. The mutation status of mismatch repair (MMR) genes was not associated with RFS. Different genomic features were found between the groups. The orders of APC, KRAS and APC, BRCA2 sequential somatic mutations were associated with clinical outcomes. The occurrence of somatic mutations in BRCA2, such as TP53 somatic mutations, affected recurrence-free survival. CONCLUSIONS: According to the evolution model, DNA damage response (DDR)-related ATM or BRCA2 somatic mutations are promising biomarkers for assessing the response of stage III CRC patients to oxaliplatin-based chemotherapy. The sequential order and co-occurring DDR somatic mutations are associated with recurrence-free survival.

CD40 Pathway and IL-2 Expression Mediate the Differential Outcome of Colorectal Cancer Patients with Different CSF1R c.1085 Genotypes.

Colony-stimulating factor 1 receptor (CSF-1R) acts as the receptor for colony stimulating factor 1, a cytokine that controls the production, differentiation, and function of macrophages. Prior studies showed cancer patients harboring germline CSF1R c.1085A>G genetic variant had better survival. Here, primary tumor samples from a stage III colorectal cancer (CRC) cohort were analyzed by a targeted gene expression assay containing 395 immune-related genes to study the immune mechanism underlying the different outcomes. CRC patients with CSF1R c.1085 genotype A_G had a better disease-free and overall survival than those with CSF1R genotype A_A. Compared to the group of patients without CSF1R variant, higher CD40LG expression, a surface marker of T cells, was found in the tumor tissues of patients with CSF1R c.1085 variant. In parallel with the higher CD40LG gene expression, immunofluorescent staining also showed more CD3+CD40L+ T cell infiltrates in tumors with CSF1R c.1085 genotype A_G. Moreover, higher IL-2 expression, known to be regulated by CD40 pathway, was also observed in tumors with CSF1R c.1085 genotype A_G than genotype A_A. Higher IL-2 expression generated by the interaction of CD40 ligand and CD40 between T cells and macrophages with CSF1R c.1085A>G variant is the potential mechanism explaining the different outcomes.

Treatment monitoring of colorectal cancer by integrated analysis of plasma concentration and sequencing of circulating tumor DNA.

Circulating cell-free DNA (cfDNA) analysis is an important tool for cancer monitoring. The patient-specific mutations identified in colorectal cancer (CRC) tissues are usually used to design the cfDNA analysis. Despite high specificity in predicting relapse, the sensitivity in most studies is around 40-50%. To improve this weakness, we designed a cfDNA panel according to the CRC genomic landscape and recurrent-specific mutations. The pathological variants in cfDNA samples from 60 CRC patients were studied by a next-generation sequencing (NGS) method incorporating the dual molecular barcode. Interestingly, patients in the disease positive group had a significantly higher cfDNA concentration than those in the disease negative group. Based on receiver operating characteristic analysis, the cfDNA concentration of 7 ng/mL was selected into the analytical workflow. The sensitivity in determining the disease status was 72.4%, which represented a considerable improvement on prior studies, and the specificity remained high at 80.6%. Compared to standard imaging and laboratory studies, earlier detection of residual disease and clinical benefits were shown on two cases by this cfDNA assay. We conclude this integrative framework of cfDNA analytical pipeline with a satisfactory sensitivity and specificity could be used in postoperative CRC surveillance.

Health inequality: a longitudinal study on geographic variations in lung cancer incidence and mortality in Taiwan.

BACKGROUND: This study is aimed toward an analysis of the variations in lung cancer incidence and mortality, adjusted by population factors (age, gender, and year), between administrative areas. METHODS: This is a retrospective study, using 2005-2014 data in each administrative area from the Taiwan Cancer Registry database organized by the Health Promotion Administration. The yearly age-standardized (overall) and crude (stratified by gender and age) incidence/mortality (and their growth rates) for each administrative area were collected and calculated. We used a mixed model to analyze the repeated measurements of yearly incidence and mortality rates and used general linear regression to analyze their growth rates. RESULTS: It was found that male and elderly populations had significantly higher lung cancer incidence and mortality in Taiwan. After adjusting for gender, age, and calendar year, there were no significant variations in incidence among the administrative areas, while the mortality in Yilan County was significantly higher than that in Taipei City (the capital city of Taiwan). On the other hand, the incidence in the female and younger population and mortality growth rates were higher. The incidence growth rate in Keelung City was significantly lower than that in Taipei City, while there were no significant variations in mortality growth rate among administrative areas. CONCLUSIONS: This study found an inequality in the lung cancer burden among cities in Taiwan, which can serve as the basis for future resource allocations for lung cancer prevention and treatment in Taiwan.

Therapeutic Opportunities of Targeting Histone Deacetylase Isoforms to Eradicate Cancer Stem Cells.

Cancer stem cells (CSCs), or tumor-initiating cells, are a small subset of cancer cells with the capacity for self-renewal and differentiation, which have been shown to drive tumor initiation, progression, and metastasis in many types of cancer. Moreover, therapeutic regimens, such as cisplatin and radiation were reported to induce the enrichment of CSCs, thereby conferring chemoresistance on cancer cells. Therefore, therapeutic targeting of CSCs represents a clinical challenge that needs to be addressed to improve patient outcome. In this context, the effectiveness of pan or class-I histone deacetylase (HDAC) inhibitors in suppressing the CSC population is especially noteworthy in light of the new paradigm of combination therapy. Evidence suggests that this anti-CSC activity is associated with the ability of HDAC inhibitors to target multiple signaling pathways at different molecular levels. Beyond chromatin remodeling via histone acetylation, HDAC inhibitors can also block key signaling pathways pertinent to CSC maintenance. Especially noteworthy is the ability of different HDAC isoforms to regulate the protein stability and/or activity of a series of epithelial-mesenchymal transition (EMT)-inducing transcription factors, including HIF-1α, Stat3, Notch1, ß-catenin, NF-κB, and c-Jun, each of which plays a critical role in regulating CSCs. From the translational perspective, these mechanistic links constitute a rationale to develop isoform-selective HDAC inhibitors as anti-CSC agents. Thus, this review aims to provide an overview on the roles of HDAC isoforms in maintaining CSC homeostasis via distinct signaling pathways independent of histone acetylation.

Health-related quality of life and cost comparison of adjuvant capecitabine versus 5-fluorouracil/leucovorin in stage III colorectal cancer patients.

PURPOSE: The purpose of this study was to compare health-related quality of life (HRQoL) and costs associated with 2 adjuvant chemotherapy regimens [capecitabine-based therapy versus 5-fluorouracil/leucovorin (5-FU/LV)-based therapy] in stage III colorectal cancer patients. METHODS: We conducted a prospective, open-label, observational, multicenter study from July 2008 to July 2011. The European Organization for Research and Treatment of Cancer QLQ-C30 and QLQ-CR38 questionnaires was used to assess HRQoL before, during, and after treatment. The direct and indirect costs of adjuvant treatment were estimated from a specially prepared questionnaire, the National Health Insurance Research Database, and other published sources. We used propensity scoring to match samples between groups and performed multivariate analyses to adjust for differences in patient demographics and clinical characteristics. RESULTS: A total of 497 patients were enrolled, and 356 completed the surveys. Following propensity score matching, 239 patients were included in the analysis (122 in the capecitabine-based group, 117 in the 5-FU/LV-based group). Global HRQoL scores did not differ significantly between the two groups. However, compared to patients in the 5-FU/LV-based group, patients in the capecitabine-based group had less nausea and vomiting (mid-term, P = 0.024; final, P = 0.013), appetite loss (mid-term, P < 0.0001; final, P = 0.001), and fewer side effects from chemotherapy (mid-term, P = 0.017). In addition, the monthly cost of capecitabine-based therapy was lower than those of 5-FU/LV-based therapy [NT$31,895.46 (US$1063.18) vs. NT$79,159.24 (US$2638.64) per patient]. CONCLUSIONS: Capecitabine is a reasonable alternative and cost-effective treatment option under current conditions for patients with stage III colorectal cancer.

Tight junction protein cingulin variant is associated with cancer susceptibility by overexpressed IQGAP1 and Rac1-dependent epithelial-mesenchymal transition.

BACKGROUND: Cingulin (CGN) is a pivotal cytoskeletal adaptor protein located at tight junctions. This study investigates the link between CGN mutation and increased cancer susceptibility through genetic and mechanistic analyses and proposes a potential targeted therapeutic approach. METHODS: In a high-cancer-density family without known pathogenic variants, we performed tumor-targeted and germline whole-genome sequencing to identify novel cancer-associated variants. Subsequently, these variants were validated in a 222 cancer patient cohort, and CGN c.3560C > T was identified as a potential cancer-risk allele. Both wild-type (WT) (c.3560C > C) and variant (c.3560C > T) were transfected into cancer cell lines and incorporated into orthotopic xenograft mice model for evaluating their effects on cancer progression. Western blot, immunofluorescence analysis, migration and invasion assays, two-dimensional gel electrophoresis with mass spectrometry, immunoprecipitation assays, and siRNA applications were used to explore the biological consequence of CGN c.3560C > T. RESULTS: In cancer cell lines and orthotopic animal models, CGN c.3560C > T enhanced tumor progression with reduced sensitivity to oxaliplatin compared to the CGN WT. The variant induced downregulation of epithelial marker, upregulation of mesenchymal marker and transcription factor, which converged to initiate epithelial-mesenchymal transition (EMT). Proteomic analysis was conducted to investigate the elements driving EMT in CGN c.3560C > T. This exploration unveiled overexpression of IQGAP1 induced by the variant, contrasting the levels observed in CGN WT. Immunoprecipitation assay confirmed a direct interaction between CGN and IQGAP1. IQGAP1 functions as a regulator of multiple GTPases, particularly the Rho family. This overexpressed IQGAP1 was consistently associated with the activation of Rac1, as evidenced by the analysis of the cancer cell line and clinical sample harboring CGN c.3560C > T. Notably, activated Rac1 was suppressed following the downregulation of IQGAP1 by siRNA. Treatment with NSC23766, a selective inhibitor for Rac1-GEF interaction, resulted in the inactivation of Rac1. This intervention mitigated the EMT program in cancer cells carrying CGN c.3560C > T. Consistently, xenograft tumors with WT CGN showed no sensitivity to NSC23766 treatment, but NSC23766 demonstrated the capacity to attenuate tumor growth harboring c.3560C > T. CONCLUSIONS: CGN c.3560C > T leads to IQGAP1 overexpression, subsequently triggering Rac1-dependent EMT. Targeting activated Rac1 is a strategy to impede the advancement of cancers carrying this specific variant.

Germline MLH1 and MSH6 mutations from two Lynch syndrome families identified in a patient with early-onset of endometrial cancer: A case report.

Introduction: Lynch syndrome is caused by a germline mutation in mismatch repair (MMR) genes, leading to the loss of expression of MMR heterodimers, either MLH1/PMS2 or MSH2/MSH6, or isolated loss of PMS2 or MSH6. Concurrent loss of both heterodimers is uncommon, and patients carrying pathogenic variants affecting different MMR genes are rare, leading to the lack of cancer screening recommendation for these patients.Case presentation:Here, we reported a female with a family history of Lynch syndrome with MLH1 c.676C > T mutation. She developed endometrial cancer at 37 years old, with loss of MLH1/PMS2 expression. Immunohistochemical staining on tumor samples incidentally detected the additional loss of MSH6 expression. Whole exome sequencing on genomic DNA from peripheral blood revealed MSH6 c.2731C > T mutation, which was confirmed to be inherited from her mother, who had an early-onset ascending colon cancer without cancer family history. Conclusion: This is a rare case of the Lynch syndrome harboring germline mutations simultaneously in two different MMR genes inherited from two families with Lynch syndrome. The diagnosis of endometrial cancer at the age less than 40 years is uncommon for Lynch syndrome-related endometrial cancer. This suggests an earlier cancer screening for patients carrying two MMR mutations.

Pathogenicity Prediction of Single Amino Acid Variants With Machine Learning Model Based on Protein Structural Energies.

The most popular tools for predicting pathogenicity of single amino acid variants (SAVs) were developed based on sequence-based techniques. SAVs may change protein structure and function. In the context of van der Waals force and disulfide bridge calculations, no method directly predicts the impact of mutations on the energies of the protein structure. Here, we combined machine learning methods and energy scores of protein structures calculated by Rosetta Energy Function 2015 to predict SAV pathogenicity. The accuracy level of our model (0.76) is higher than that of six prediction tools. Further analyses revealed that the differential reference energies, attractive energies, and solvation of polar atoms between wildtype and mutant side-chains played essential roles in distinguishing benign from pathogenic variants. These features indicated the physicochemical properties of amino acids, which were observed in 3D structures instead of sequences. We added 16 features to Rhapsody (the prediction tool we used for our data set) and consequently improved its performance. The results indicated that these energy scores were more appropriate and more detailed representations of the pathogenicity of SAVs.

Slice-Fusion: Reducing False Positives in Liver Tumor Detection for Mask R-CNN.

Automatic liver tumor detection from computed tomography (CT) makes clinical examinations more accurate. However, deep learning-based detection algorithms are characterized by high sensitivity and low precision, which hinders diagnosis given that false-positive tumors must first be identified and excluded. These false positives arise because detection models incorrectly identify partial volume artifacts as lesions, which in turn stems from the inability to learn the perihepatic structure from a global perspective. To overcome this limitation, we propose a novel slice-fusion method in which mining the global structural relationship between the tissues in the target CT slices and fusing the features of adjacent slices according to the importance of the tissues. Furthermore, we design a new network based on our slice-fusion method and Mask R-CNN detection model, called Pinpoint-Net. We evaluated proposed model on the Liver Tumor Segmentation Challenge (LiTS) dataset and our liver metastases dataset. Experiments demonstrated that our slice-fusion method not only enhance tumor detection ability via reducing the number of false-positive tumors smaller than 10mm, but also improve segmentation performance. Without bells and whistles, a single Pinpoint-Net showed outstanding performance in liver tumor detection and segmentation on LiTS test dataset compared with other state-of-the-art models.