Death-associated protein-3, DAP-3, correlates with preoperative chemotherapy effectiveness and prognosis of gastric cancer patients following perioperative chemotherapy and radical gastrectomy

A decision support system to recommend appropriate therapy protocol for AML patients

Introduction

Acute Myeloid Leukemia (AML) is one of the most aggressive hematological neoplasms, emphasizing the critical need for early detection and strategic treatment planning. The association between prompt intervention and enhanced patient survival rates underscores the pivotal role of therapy decisions. To determine the treatment protocol, specialists heavily rely on prognostic predictions that consider the response to treatment and clinical outcomes. The existing risk classification system categorizes patients into favorable, intermediate, and adverse groups, forming the basis for personalized therapeutic choices. However, accurately assessing the intermediate-risk group poses significant challenges, potentially resulting in treatment delays and deterioration of patient conditions.

Methods

This study introduces a decision support system leveraging cutting-edge machine learning techniques to address these issues. The system automatically recommends tailored oncology therapy protocols based on outcome predictions.

Results

The proposed approach achieved a high performance close to 0.9 in F1-Score and AUC. The model generated with gene expression data exhibited superior performance.

Discussion

Our system can effectively support specialists in making well-informed decisions regarding the most suitable and safe therapy for individual patients. The proposed decision support system has the potential to not only streamline treatment initiation but also contribute to prolonged survival and improved quality of life for individuals diagnosed with AML. This marks a significant stride toward optimizing therapeutic interventions and patient outcomes.

Nomogram for predicting pathological response to neoadjuvant treatment in patients with locally advanced gastric cancer: Data from a phase III clinical trial

PURPOSE

This study aimed to establish a nomogram using routinely available clinicopathological parameters to predict the pathological response in patients with locally advanced gastric cancer (LAGC) undergoing neoadjuvant treatment.

MATERIALS AND METHODS

We conducted this study based on the ongoing Neo-CRAG trial, a prospective study focused on preoperative treatment in patients with LAGC. A total of 221 patients who underwent surgery following neoadjuvant chemotherapy (nCT) or neoadjuvant chemoradiotherapy (nCRT) at Sun Yat-sen University Cancer Center between June 2013 and July 2022 were included in the analysis. We defined complete or near-complete pathological regression and ypN0 as good response (GR), and determined the prognostic value of GR by Kaplan-Meier survival analysis. Eventually, a nomogram for predicting GR was developed based on statistically identified predictors through multivariate logistic regression analysis and internally validated by the bootstrap method.

RESULTS

GR was confirmed in 54 patients (54/221, 24.4%). Patients who achieved GR had a longer progression-free survival and overall survival. Then, five independent factors, including pretreatment tumor differentiation, clinical T stage, monocyte count, CA724 level, and the use of nCRT, were identified. Based on these predictors, the nomogram was established with an area under the curve (AUC) of 0.777 (95% CI, 0.705-0.850) and a bias-corrected AUC of 0.752.

CONCLUSION

A good pathological response after neoadjuvant treatment was associated with an improved prognosis in LAGC patients. The nomogram we established exhibits a high predictive capability for GR, offering potential value in devising personalized and precise treatment strategies for LAGC patients.

Death-associated protein 3 in cancer-discrepant roles of DAP3 in tumours and molecular mechanisms

Cancer, ranks as the secondary cause of death, is a group of diseases that are characterized by uncontrolled tumor growth and distant metastasis, leading to increased mortality year-on-year. To date, targeted therapy to intercept the aberrant proliferation and invasion is crucial for clinical anticancer treatment, however, mutant expression of target genes often leads to drug resistance. Therefore, it is essential to identify more molecules that can be targeted to facilitate combined therapy. Previous studies showed that death associated protein 3 (DAP3) exerts a pivotal role in regulating apoptosis signaling of tumors, meanwhile, aberrant DAP3 expression is associated with the tumorigenesis and disease progression of various cancers. This review provides an overview of the molecule structure of DAP3 and the discrepant roles played by DAP3 in various types of tumors. Considering the molecular mechanism of DAP3-regulated cancer development, new potential treatment strategies might be developed in the future.

Imaging advances in efficacy assessment of gastric cancer neoadjuvant chemotherapy

Effective neoadjuvant chemotherapy (NAC) can improve the survival of patients with locally progressive gastric cancer, but chemotherapeutics do not always exhibit good efficacy in all patients. Therefore, accurate preoperative evaluation of the effect of neoadjuvant therapy and the appropriate selection of surgery time to minimize toxicity and complications while prolonging patient survival are key issues that need to be addressed. This paper reviews the role of three imaging methods, morphological, functional, radiomics, and artificial intelligence (AI)-based imaging, in evaluating NAC pathological reactions for gastric cancer. In addition, the advantages and disadvantages of each method and the future application prospects are discussed.

Activated Leukocyte Cell Adhesion Molecule (ALCAM), a Potential 'Seed' and 'Soil' Receptor in the Peritoneal Metastasis of Gastrointestinal Cancers

Activated Leukocyte Cell Adhesion Molecule (ALCAM/CD166) is a cell-cell adhesion protein conferring heterotypic and homotypic interactions between cells of the same type and different types. It is aberrantly expressed in various cancer types and has been shown to be a regulator of cancer metastasis. In the present study, we investigated potential roles of ALCAM in the peritoneal transcoelomic metastasis in gastrointestinal cancers, a metastatic type commonly occurred in gastro-intestinal and gynaecological malignancies and resulting in poor clinical outcomes. Specifically, we studied whether ALCAM acts as both a 'seed' receptor in these tumour cells and a 'soil' receptor in peritoneal mesothelial cells during cancer metastasis. Gastric cancer and pancreatic cancer tissues with or without peritoneal metastasis were compared for their levels of ALCAM expression. The impact of ALCAM expression in these tumours was also correlated to the patients' clinical outcomes, namely peritoneal metastasis-free survival. In addition, cancer cells of gastric and pancreatic origins were used to create cell models with decreased or increased levels of ALCAM expression by genetic knocking down or overexpression, respectively. Human peritoneal mesothelial cells were also genetically transfected to generate cell models with different profiles of ALCAM expression. These cell models were used in the tumour-mesothelial interaction assay to assess if and how the interaction was influenced by ALCAM. Both gastric and pancreatic tumour tissues from patients who developed peritoneal metastases had higher levels of ALCAM transcript than those without. Patients who had tumours with high levels of ALCAM had a much shorter peritoneal metastasis free survival compared with those who had low ALCAM expression (p = 0.006). ALCAM knockdown of the mesothelial cell line MET5A rendered the cells with reduced interaction with both gastric cancer cells and pancreatic cancer cells. Likewise, levels of ALCAM in both human gastric and pancreatic cancer cells were also a determining factor for their adhesiveness to mesothelial cells, a process that was likely to be triggered the phosphorylation of the SRC kinase. A soluble ALCAM (sALCAM) was found to be able to inhibit the adhesiveness between cancer cells and mesothelial cells, mechanistically behaving like a SRC kinase inhibitor. ALCAM is an indicator of peritoneal metastasis in both gastric and pancreatic cancer patients. It acts as not only a potential peritoneal 'soil' receptor of tumour seeding but also a 'soil' receptor in peritoneal mesothelial cells during cancer metastasis. These findings have an important therapeutic implication for treating peritoneal transcoelomic metastases.

Mitochondrial ribosomal small subunit (MRPS) MRPS23 protein-protein interaction reveals phosphorylation by CDK11-p58 affecting cell proliferation and knockdown of MRPS23 sensitizes breast cancer cells to CDK1 inhibitors

BACKGROUND

Post-translational modification of some mitoribosomal proteins has been found to regulate their functions. MRPS23 has been reported to be overexpressed in various cancers and has been predicted to be involved in increased cell proliferation. Furthermore, MRPS23 is a driver of luminal subtype breast cancer. However, its exact role and function in cancer remains unknown. METHODS AND RESULTS: Our previous study identified protein-protein interactions involving MRPS23 and CDK11A. In this study, we confirmed the interaction of MRPS23 with the p110 and p58 isoforms of CDK11A. Phosphoprotein enrichment studies and in vitro kinase assay using CDK11A/cyclin D3 followed by MALDI-ToF/ToF analysis confirmed the phosphorylation of MRPS23 at N-terminal serine 11 residue. Breast cancer cells expressing the MRPS23 (S11G) mutant showed increased cell proliferation, increased expression of PI3-AKT pathway proteins [p-AKT (Ser47), p-AKT (Thr308), p-PDK (Ser241) and p-GSK-3β (Ser9)] and increased antiapoptotic pathway protein expression [Bcl-2, Bcl-xL, p-Bcl2 (Ser70) and MCL-1] when compared with the MRPS23 (S11A) mutant-overexpressing cells. This finding indicated the role of MRPS23 phosphorylation in the proliferation and survival of breast cancer cells. The correlation of inconsistent MRPS23 phosphoserine 11 protein expression with CDK11A in the breast cancer cells suggested phosphorylation by other kinases. In vitro kinase assay showed that CDK1 kinase also phosphorylated MRPS23 and that inhibition using CDK1 inhibitors lowered phospho-MRPS23 (Ser11) levels. Additionally, modulating the expression of MRPS23 altered the sensitivity of the cells to CDK1 inhibitors.

CONCLUSION

In conclusion, phosphorylation of MRPS23 by mitotic kinases might potentially be involved in the proliferation of breast cancer cells. Furthermore, MRPS23 can be targeted for sensitizing the breast cancer cells to CDK1 inhibitors.

Potential of Mitochondrial Ribosomal Genes as Cancer Biomarkers Demonstrated by Bioinformatics Results

Next-generation sequencing and bioinformatics analyses have clearly revealed the roles of mitochondrial ribosomal genes in cancer development. Mitochondrial ribosomes are composed of three RNA components encoded by mitochondrial DNA and 82 specific protein components encoded by nuclear DNA. They synthesize mitochondrial inner membrane oxidative phosphorylation (OXPHOS)-related proteins and participate in various biological activities via the regulation of energy metabolism and apoptosis. Mitochondrial ribosomal genes are strongly associated with clinical features such as prognosis and foci metastasis in patients with cancer. Accordingly, mitochondrial ribosomes have become an important focus of cancer research. We review recent advances in bioinformatics research that have explored the link between mitochondrial ribosomes and cancer, with a focus on the potential of mitochondrial ribosomal genes as biomarkers in cancer.

A CT-based deep learning radiomics nomogram for predicting the response to neoadjuvant chemotherapy in patients with locally advanced gastric cancer: A multicenter cohort study

BACKGROUND

Accurate prediction of treatment response to neoadjuvant chemotherapy (NACT) in individual patients with locally advanced gastric cancer (LAGC) is essential for personalized medicine. We aimed to develop and validate a deep learning radiomics nomogram (DLRN) based on pretreatment contrast-enhanced computed tomography (CT) images and clinical features to predict the response to NACT in patients with LAGC.

METHODS

719 patients with LAGC were retrospectively recruited from four Chinese hospitals between Dec 1st, 2014 and Nov 30th, 2020. The training cohort and internal validation cohort (IVC), comprising 243 and 103 patients, respectively, were randomly selected from center I; the external validation cohort1 (EVC1) comprised 207 patients from center II; and EVC2 comprised 166 patients from another two hospitals. Two imaging signatures, reflecting the phenotypes of the deep learning and handcrafted radiomics features, were constructed from the pretreatment portal venous-phase CT images. A four-step procedure, including reproducibility evaluation, the univariable analysis, the LASSO method, and the multivariable logistic regression analysis, was applied for feature selection and signature building. The integrated DLRN was then developed for the added value of the imaging signatures to independent clinicopathological factors for predicting the response to NACT. The prediction performance was assessed with respect to discrimination, calibration, and clinical usefulness. Kaplan-Meier survival curves based on the DLRN were used to estimate the disease-free survival (DFS) in the follow-up cohort (n = 300).

FINDINGS

The DLRN showed satisfactory discrimination of good response to NACT and yielded the areas under the receiver operating curve (AUCs) of 0.829 (95% CI, 0.739-0.920), 0.804 (95% CI, 0.732-0.877), and 0.827 (95% CI, 0.755-0.900) in the internal and two external validation cohorts, respectively, with good calibration in all cohorts (p > 0.05). Furthermore, the DLRN performed significantly better than the clinical model (p < 0.001). Decision curve analysis confirmed that the DLRN was clinically useful. Besides, DLRN was significantly associated with the DFS of patients with LAGC (p < 0.05).

INTERPRETATION

A deep learning-based radiomics nomogram exhibited a promising performance for predicting therapeutic response and clinical outcomes in patients with LAGC, which could provide valuable information for individualized treatment.

Biomarker evaluation in radically resectable locally advanced gastric cancer treated with neoadjuvant chemotherapy: an evidence reappraisal

Neoadjuvant chemotherapy (NAC) significantly improved the prognosis of patients with locally advanced resectable gastric cancer but, despite important progresses, relapse-related death remains a major challenge. Therefore, it appears crucial to understand which patients will benefit from peri-operative treatment. Biomarkers such as human epidermal growth factor receptor-2 (HER2), microsatellite instability (MSI), and Epstein-Barr Virus (EBV) have been widely studied; however, they do not yet guide the choice of perioperative treatment in clinical practice. We performed a narrative review, including 23 studies, addressing the value of tissue- or blood-based biomarkers in the neoadjuvant setting. Ten studies (43.5%) were prospective, and more than half were conducted in East-Asia. Biomarkers were evaluated only post-NAC (on surgical samples or blood) in seven studies (30.4%), only pre-NAC (on endoscopic specimens or blood) in 10 studies (43.5%), and both pre- and post-NAC (26.1%) in six studies. Among the high variety of investigated biomarkers, some of these including MSI-H or enzymatic profile (as TS, UGT1A1, MTHFR, ERCC or XRCC) showed promising results and deserve to be assessed in methodologically sound clinical trials. The identification of molecular biomarkers in patients treated with NAC for locally advanced resectable gastric or EGJ cancer remains crucial.

Development and Validation of a Computed Tomography-Based Radiomics Signature to Predict Response to Neoadjuvant Chemotherapy for Locally Advanced Gastric Cancer

IMPORTANCE

Neoadjuvant therapies have been shown to decrease tumor burden, increase resection rate, and improve the outcomes among patients with locally advanced gastric cancer (GC). However, not all patients are equally responsive; therefore, differentiating potential respondents from nonrespondents is clinically important.

OBJECTIVE

To use pretreatment computed tomography (CT)-pixelated feature-difference extraction techniques to identify diagnostically relevant features that could predict patients' response to neoadjuvant chemotherapy at diagnosis.

DESIGN, SETTING, AND PARTICIPANTS

This multicenter cohort study included patients with locally advanced GC who were treated from January 2010 to July 2017 at 2 hospitals in southern China (training cohort) and 1 hospital in northern China (external validation cohort). Their clinicopathological data, pretreatment CT images, and pathological reports were retrieved and analyzed. Data analysis was conducted from December 2017 to May 2021.

EXPOSURES

All patients underwent 2 to 4 cycles of fluorouracil in combination with a platinum-based neoadjuvant chemotherapy regimen. All gastrectomies were performed according to the Japanese Classification of Gastric Carcinoma (14th edition) guidelines.

MAIN OUTCOMES AND MEASURES

Reliability of clinicopathological and radiomics-based features were assessed with area under receiver operating characteristic curve (AUC) and Mann-Whitney U test.

RESULTS

A total of 323 patients (242 [74.9%] men; median [range] age, 58 [24-82] years) were included in the study, with 250 patients (77.4%) in the training cohort and 73 (22.6%) in the validation cohort. The baseline pretreatment characteristics of the training and validation cohorts were well-balanced. The number of respondents in the training and validation cohort was 122 (48.8%) and 40 (54.8%), respectively, and the number of nonrespondents was 128 (51.2%) and 33 (45.2%), respectively. No clinicopathological variables were significantly associated with treatment response. Using radiomics, 20 low-intercorrelated features from a total of 7477 features were used to construct a radiomics signature that demonstrated significant association with treatment response. Good discrimination performance of the radiomics signature for predicting treatment response in the training (AUC, 0.736; 95% CI, 0.675-0.798) and external validation (AUC, 0.679; 95% CI, 0.554-0.803) cohorts was observed. Decision curve analysis confirmed the clinical utility of the radiomics signature.

CONCLUSIONS AND RELEVANCE

In this study, the proposed radiomics signature showed potential as a clinical aid for predicting the response of patients with locally advanced GC before treatment, thereby allowing timely planning for effective treatments for potential nonrespondents.

Mitochondrial ribosomal small subunit proteins (MRPS) MRPS6 and MRPS23 show dysregulation in breast cancer affecting tumorigenic cellular processes

Human Mitoribosomal Small Subunit unit (MRPS) family of genes appears to have role in cancer. Gene expression analysis of select MRPS genes (n = 9) in 15 cancer cell lines showed altered expression in cancer cells. Protein levels of MRPS6, MRPS23 showed significant overexpression in breast cancer cells and tissues. Interestingly, their overexpression did not correlate with mitochondrial ribosome translated COX2 protein levels in breast cancer. Subcellular fractionation analysis showed a distinct presence of MRPS23 in the nuclear fraction. GST/MRP6 and GST/MRPS23 pulldown assays identified 32 novel protein-protein interactions (PPIs) and MRPS23-RIPK3 interaction was validated. Co-expression module identification tool (CEMi) analysis of breast cancer gene expression and MRPS6 and MRPS23 interactions revealed hub interactions in gene expression modules having functional roles in cancer-associated cellular processes. Based on PPI network analysis a novel interaction MRPS23-p53 was validated. Knockdown of MRPS6 and MRPS23 decreased proliferation, expression of select mesenchymal markers, oncogenes, and increased expression of tumor suppressor genes. Taken together present study has revealed that MRPS6 and MRPS23 genes have pro-tumorigenic functions in breast cancer.

EPLIN Expression in Gastric Cancer and Impact on Prognosis and Chemoresistance

Epithelial protein lost in neoplasm (EPLIN) has been implicated as a suppressor of cancer progression. The current study explored EPLIN expression in clinical gastric cancer and its association with chemotherapy resistance. EPLIN transcript expression, in conjunction with patient clinicopathological information and responsiveness to neoadjuvant chemotherapy (NAC), was explored in two gastric cancer cohorts collected from the Beijing Cancer Hospital. Kaplan-Meier survival analysis was undertaken to explore EPLIN association with patient survival. Reduced EPLIN expression was associated with significant or near significant reductions of overall, disease-free, first progression or post-progression survival in the larger host cohort and Kaplan Meier plotter datasets. In the larger cohort EPLIN expression was significantly higher in the combined T1 + T2 gastric cancer group compared to the T3 + T4 group and identified to be an independent prognostic factor of disease-free survival and overall survival by multivariate analysis. In the smaller, NAC cohort, EPLIN expression was found to be significantly lower in tumour tissues than in paratumour tissues. EPLIN expression was significantly associated with responsiveness to chemotherapy which contributes to overall survival. Together, EPLIN appears to be a prognostic factor and may be associated with patient sensitivity to NAC.

Expression and affinity purification of recombinant mammalian Mitochondrial Ribosomal Small Subunit (MRPS) proteins and protein-protein interaction analysis indicate putative role in tumorigenic cellular processes

MRPS group of proteins are structural constituents of the small subunit of mitoribosomes involved in translation. Recent studies indicate role in tumorigenic process, however, unlike cytosolic ribosomal proteins, knowledge on the role of MRPS proteins in alternate cellular processes is very limited. Mapping protein-protein interactions (PPIs) onto known cellular processes can be a valuable tool to identify novel protein functions. In this study, to identify PPIs of MRPS proteins, we have constructed thirty-one GST/MRPS fusion clones. GST/MRPS fusion proteins were confirmed by MALDI-TOF analysis. GST pull-downs were performed using eight GST/MRPS proteins (MRPS9, MRPS10, MRPS11, MRPS18B, MRPS31, MRPS33, MRPS38, MRPS39), GST alone as pull-down control, and HEK293 cell lysate as the source for anchor proteins followed by nLC/MS/MS analysis and probable PPIs of eight MRPS proteins were identified. Three PPIs from GST pull-downs and interaction between six MRPS proteins and p53 previously reported in PPI database were validated. The PPI network analysis revealed putative role in cellular processes with implications for tumorigenesis. Gene expression screening of a cancer cell line panel indicated overexpression of MRPS10 and MRPS31 in breast cancer. Co-expression module identification tool analysis of breast cancer gene expression and MRPS10 and MRPS31 PPIs revealed putative role for PPI with ACADSB in fatty acid oxidation process regulated by brain-derived neurotrophic factor (BDNF) signaling pathway.

Histologic Lymph Nodes Regression after Preoperative Chemotherapy as Prognostic Factor in Non-metastatic Advanced Gastric Adenocarcinoma

Background: The study aims to evaluate the lymph node (LN) response to preoperative chemotherapy and its impact on long-term outcomes in advanced gastric cancer (AGC).

Methods: Histological specimens retrieved at gastrectomy from patients who received preoperative chemotherapy were evaluated. LN regression was graded by the adapted tumor regression grading system proposed by Becker. Patients were classified as node-negative (lnNEG) in the case of all negative LN without evidence of previous tumor involvement. Patients with LN metastasis were classified as nodal responders (lnR) in case of a regression score 1a-2 was detected in the LN. Nodal non-responders (lnNR) had a regression score of 3 in all of the metastatic nodes. Survival was compared using Kaplan-Meier and Cox regression analysis.

Results:Among 87 patients included in the final analysis 29.9 % were lnNEG, 21.8 % were lnR and 48.3 % were lnNR. Kaplan-Meier curves showed a survival benefit for lnR over lnNR (p=0.03), while the survival of lnR and lnNEG patients was similar. Cox regression confirmed nodal response to be associated with decreased odds for death in univariate (HR: 0.33; 95 % CI 0.11-0.96, p=0.04) and multivariable (HR 0.37; 95 CI% 0.14-0.99, p=0.04) analysis.

Conclusions: Histologic regression of LN metastasis after preoperative chemotherapy predicts the increased survival of patients with non-metastatic resectable AGC.

Neoadjuvant therapy for locally advanced gastric cancer patients. A population pharmacodynamic modeling

Background

Perioperative chemotherapy (CT) or neoadjuvant chemoradiotherapy (CRT) in patients with locally advanced gastric (GC) or gastroesophageal junction cancer (GEJC) has been shown to improve survival compared to an exclusive surgical approach. However, most patients retain a poor prognosis due to important relapse rates. Population pharmacokinetic-pharmacodynamic (PK/PD) modeling may allow identifying at risk-patients. We aimed to develop a mechanistic PK/PD model to characterize the relationship between the type of neoadjuvant therapy, histopathologic response and survival times in locally advanced GC and GEJC patients.

Methods

Patients with locally advanced GC and GEJC treated with neoadjuvant CT with or without preoperative CRT were analyzed. Clinical response was assessed by CT-scan and EUS. Pathologic response was defined as a reduction on pTNM stage compared to baseline cTNM. Metastasis development risk and overall survival (OS) were described using the population approach with NONMEM 7.3. Model evaluation was performed through predictive checks.

Results

A low correlation was observed between clinical and pathologic TNM stage for both T (R = 0.32) and N (R = 0.19) categories. A low correlation between clinical and pathologic response was noticed (R = -0.29). The OS model adequately described the observed survival rates. Disease recurrence, cTNM stage ≥3 and linitis plastica absence, were correlated to a higher risk of death.

Conclusion

Our model adequately described clinical response profiles, though pathologic response could not be predicted. Although the risk of disease recurrence and survival were linked, the identification of alternative approaches aimed to tailor therapeutic strategies to the individual patient risk warrants further research.

Depletion of death-associated protein-3 induces chemoresistance in gastric cancer cells through the β-catenin/LGR5/Bcl-2 axis

Previously, we demonstrated that death-associated protein-3 (DAP3) loss drives chemoresistance in gastric cancer cells. In the present study, we aimed to determine the underlying molecular mechanism. The effect of DAP3 silencing on β-catenin signaling was assessed. The direct mediator of DAP3 silencing-induced chemoresistance was identified. Depletion of DAP3 stimulates nuclear accumulation of β-catenin and enhances β-catenin-dependent transcriptional activity in gastric cancer cells. However, the protein kinase B , , extracellular regulated protein kinase and signal transducer and activator of transcription 3 signaling pathways remain unaffected by DAP3 loss. We found that the downstream target gene LGR5 (leucine-rich G-protein coupled receptor 5) is upregulated in DAP3-depleted gastric cancer cells. Moreover, knockdown of LGR5 resensitizes DAP3-depleted gastric cancer cells to 5-fluorouracil (5-FU) and oxaliplatin. We also observed that ectopic expression of LGR5 reduces apoptosis in gastric cancer cells on treatment with 5-FU and oxaliplatin, which is accompanied by prevention of caspase-3 cleavage. The antiapoptotic protein Bcl-2 is identified as a key mediator of LGR5-induced apoptosis resistance in gastric cancer cells. The present findings indicate that DAP3 deficiency-induced chemoresistance in gastric cancer is at least partially mediated through the β-catenin/LGR5/Bcl-2 axis. Targeting LGR5 may provide a novel strategy to overcome chemoresistance in DAP3-deficient gastric cancer cells.

Mutation, methylation, and gene expression profiles in dup(1q)-positive pediatric B-cell precursor acute lymphoblastic leukemia

High-throughput sequencing was applied to investigate the mutation/methylation patterns on 1q and gene expression profiles in pediatric B-cell precursor acute lymphoblastic leukemia (BCP ALL) with/without (w/wo) dup(1q). Sequencing of the breakpoint regions and all exons on 1q in seven dup(1q)-positive cases revealed non-synonymous somatic single nucleotide variants (SNVs) in BLZF1, FMN2, KCNT2, LCE1C, NES, and PARP1. Deep sequencing of these in a validation cohort w (n = 17)/wo (n = 94) dup(1q) revealed similar SNV frequencies in the two groups (47% vs. 35%; P = 0.42). Only 0.6% of the 36,259 CpGs on 1q were differentially methylated between cases w (n = 14)/wo (n = 13) dup(1q). RNA sequencing of high hyperdiploid (HeH) and t(1;19)(q23;p13)-positive cases w (n = 14)/wo (n = 52) dup(1q) identified 252 and 424 differentially expressed genes, respectively; only seven overlapped. Of the overexpressed genes in the HeH and t(1;19) groups, 23 and 31%, respectively, mapped to 1q; 60-80% of these encode nucleic acid/protein binding factors or proteins with catalytic activity. We conclude that the pathogenetically important consequence of dup(1q) in BCP ALL is a gene-dosage effect, with the deregulated genes differing between genetic subtypes, but involving similar molecular functions, biological processes, and protein classes.

Approaches and genetic determinants in predicting response to neoadjuvant chemotherapy in locally advanced gastric cancer

Gastric cancer remains a major health burden worldwide. There is near-universal agreement that neoadjuvant chemotherapy (NAC) is a preferred management for locally advanced gastric cancer (LAGC). However, the optimal approach for an individual patient is still not clear and remains controversial, which could be at least partly explained by the lack of predictive tools. The ability to predict chemosensitivity from NAC in routine clinical practice is difficult and is an area of intense investigation, especially in the Precision-Medicine Era. Available consistent evidence suggests that a favorable tumor histopathological response to NAC may be a useful positive prognostic marker in gastric cancer. Hence, it is reasonable to speculate that making the histopathological response from NAC predictable will dramatically facility the NAC and improve patients' outcome. This review provides an overview on the current status of predictive biomarkers for histopathological response from NAC in LAGC, including clinicopathological variables, imaging and molecular testing. Furthermore, limitations and future perspectives are also discussed.

Mitochondrial ribosomes in cancer

Mitochondria play fundamental roles in the regulation of life and death of eukaryotic cells. They mediate aerobic energy conversion through the oxidative phosphorylation (OXPHOS) system, and harbor and control the intrinsic pathway of apoptosis. As a descendant of a bacterial endosymbiont, mitochondria retain a vestige of their original genome (mtDNA), and its corresponding full gene expression machinery. Proteins encoded in the mtDNA, all components of the multimeric OXPHOS enzymes, are synthesized in specialized mitochondrial ribosomes (mitoribosomes). Mitoribosomes are therefore essential in the regulation of cellular respiration. Additionally, an increasing body of literature has been reporting an alternative role for several mitochondrial ribosomal proteins as apoptosis-inducing factors. No surprisingly, the expression of genes encoding for mitoribosomal proteins, mitoribosome assembly factors and mitochondrial translation factors is modified in numerous cancers, a trait that has been linked to tumorigenesis and metastasis. In this article, we will review the current knowledge regarding the dual function of mitoribosome components in protein synthesis and apoptosis and their association with cancer susceptibility and development. We will also highlight recent developments in targeting mitochondrial ribosomes for the treatment of cancer.

Preoperative Chemotherapy for Gastric Cancer: Personal Interventions and Precision Medicine

In spite of the declining incidence of gastric cancer (GC) in recent years, the mortality rate is still high. The asymptomatic nature and nonspecific clinical manifestations combined with the lack of efficient screening programs delay the diagnosis of GC. Therefore, the prevalence of advanced gastric cancer (AGC) has prompted the need for aggressive and intensive treatment options. Among the various treatment options for AGC, surgery is still the mainstay. However, the efficacy of surgery alone is not established. Results from multiple randomized controlled trials suggest that preoperative chemotherapy is promising intervention for the treatment and management of AGC. The main objective of neoadjuvant chemotherapy is to downstage or control micrometastasis in resectable tumor before surgery. On the other hand, conversion chemotherapy refers to surgical treatment aiming at R0 resection after chemotherapy for originally nonresectable or marginally resectable tumors. Nevertheless, preoperative chemoradiotherapy is considered beneficial for AGC patients. Over the last few decades, the combination of chemotherapy and targeted therapy prior to surgery demonstrated great results for the treatment of AGC. The rapid developments in genomics and proteomics have heralded the era of precision medicine. The combination of preoperative chemotherapy and precision medicine may enhance survival in AGC patients.

The intron-enriched HERV-K(HML-10) family suppresses apoptosis, an indicator of malignant transformation

Background

Human endogenous retroviruses (HERVs) constitute 8% of the human genome and contribute substantially to the transcriptome. HERVs have been shown to generate RNAs that modulate host gene expression. However, experimental evidence for an impact of these regulatory transcripts on the cellular phenotype has been lacking.

Results

We characterized the previously little described HERV-K(HML-10) endogenous retrovirus family on a genome-wide scale. HML-10 invaded the ancestral genome of Old World monkeys about 35 Million years ago and is enriched within introns of human genes when compared to other HERV families. We show that long terminal repeats (LTRs) of HML-10 exhibit variable promoter activity in human cancer cell lines. One identified HML-10 LTR-primed RNA was in opposite orientation to the pro-apoptotic Death-associated protein 3 (DAP3). In HeLa cells, experimental inactivation of HML-10 LTR-primed transcripts induced DAP3 expression levels, which led to apoptosis.

Conclusions

Its enrichment within introns suggests that HML-10 may have been evolutionary co-opted for gene regulation more than other HERV families. We demonstrated such a regulatory activity for an HML-10 RNA that suppressed DAP3-mediated apoptosis in HeLa cells. Since HML-10 RNA appears to be upregulated in various tumor cell lines and primary tumor samples, it may contribute to evasion of apoptosis in malignant cells. However, the overall weak expression of HML-10 transcripts described here raises the question whether our result described for HeLa represent a rare event in cancer. A possible function in other cells or tissues requires further investigation.

Electronic supplementary material

The online version of this article (doi:10.1186/s13100-016-0081-9) contains supplementary material, which is available to authorized users.