Multi-omics characterization of molecular features of gastric cancer correlated with response to neoadjuvant chemotherapy

Deep learning nomogram for predicting neoadjuvant chemotherapy response in locally advanced gastric cancer patients

PURPOSE

Developed and validated a deep learning radiomics nomogram using multi-phase contrast-enhanced computed tomography (CECT) images to predict neoadjuvant chemotherapy (NAC) response in locally advanced gastric cancer (LAGC) patients.

METHODS

This multi-center study retrospectively included 322 patients diagnosed with gastric cancer from January 2013 to June 2023 at two hospitals. Handcrafted radiomics technique and the EfficientNet V2 neural network were applied to arterial, portal venous, and delayed phase CT images to extract two-dimensional handcrafted and deep learning features. A nomogram model was built by integrating the handcrafted signature, the deep learning signature, with clinical features. Discriminative ability was assessed using the receiver operating characteristics (ROC) curve and the precision-recall (P-R) curve. Model fitting was evaluated using calibration curves, and clinical utility was assessed through decision curve analysis (DCA).

RESULTS

The nomogram exhibited excellent performance. The area under the ROC curve (AUC) was 0.848 [95% confidence interval (CI), 0.793-0.893)], 0.802 (95% CI 0.688-0.889), and 0.751 (95% CI 0.652-0.833) for the training, internal validation, and external validation sets, respectively. The AUCs of the P-R curves were 0.838 (95% CI 0.756-0.895), 0.541 (95% CI 0.329-0.740), and 0.556 (95% CI 0.376-0.722) for the corresponding sets. The nomogram outperformed the clinical model and handcrafted signature across all sets (all P < 0.05). The nomogram model demonstrated good calibration and provided greater net benefit within the relevant threshold range compared to other models.

CONCLUSION

This study created a deep learning nomogram using CECT images and clinical data to predict NAC response in LAGC patients undergoing surgical resection, offering personalized treatment insights.

Early Immune Remodeling Steers Clinical Response to First-Line Chemoimmunotherapy in Advanced Gastric Cancer

Adding anti-programmed cell death protein 1 (anti-PD-1) to 5-fluorouracil (5-FU)/platinum improves survival in some advanced gastroesophageal adenocarcinomas (GEA). To understand the effects of chemotherapy and immunotherapy, we conducted a phase II first-line trial (n = 47) sequentially adding pembrolizumab to 5-FU/platinum in advanced GEA. Using serial biopsy of the primary tumor at baseline, after one cycle of 5-FU/platinum, and after the addition of pembrolizumab, we transcriptionally profiled 358,067 single cells to identify evolving multicellular tumor microenvironment (TME) networks. Chemotherapy induced early on-treatment multicellular hubs with tumor-reactive T-cell and M1-like macrophage interactions in slow progressors. Faster progression featured increased MUC5A and MSLN containing treatment resistance programs in tumor cells and M2-like macrophages with immunosuppressive stromal interactions. After pembrolizumab, we observed increased CD8 T-cell infiltration and development of an immunity hub involving tumor-reactive CXCL13 T-cell program and epithelial interferon-stimulated gene programs. Strategies to drive increases in antitumor immune hub formation could expand the portion of patients benefiting from anti-PD-1 approaches.

SIGNIFICANCE

The benefit of 5-FU/platinum with anti-PD-1 in first-line advanced gastric cancer is limited to patient subgroups. Using a trial with sequential anti-PD-1, we show coordinated induction of multicellular TME hubs informs the ability of anti-PD-1 to potentiate T cell-driven responses. Differential TME hub development highlights features that underlie clinical outcomes. This article is featured in Selected Articles from This Issue, p. 695.

Morphometric analysis of nuclear shape irregularity as a novel predictor of programmed death-ligand 1 expression in lung squamous cell carcinoma

Immune checkpoint inhibitor (ICI) therapy has been established as one of the key treatment strategies for lung squamous cell carcinoma (LUSQ). The status of programmed death-ligand 1 (PD-L1) in tumor cells and/or immune cells using immunohistochemistry has been primarily used as a surrogate marker for determining ICI treatment; however, when the tissues to be examined are small, false-negative results could be unavoidable due to the heterogeneity of PD-L1 immunoreactivity. To overcome this practical limitation, we attempted to explore the status of nuclear atypia evaluated using morphometry as a potential predictor of PD-L1 status in LUSQ. We correlated the parameters related to nuclear atypia with PD-L1 status using two different cohorts of LUSQ patients (95 cases from The Cancer Genome Atlas database and 30 cases from the Miyagi Cancer Center). Furthermore, we studied the gene mutation status to elucidate the genetic profile of PD-L1 predictable cases. The results revealed that nuclear atypia, especially morphometric parameters related to nuclear shape irregularity, including aspect ratio, circularity, roundness, and solidity, were all significantly associated with PD-L1 status. Additionally, LUSQ cases with high PD-L1 expression and pronounced nuclear atypia were significantly associated with C10orf71 and COL14A1 mutations compared with those with low PD-L1 expression and mild nuclear atypia. We demonstrated for the first time that nuclear shape irregularity could represent a novel predictor of PD-L1 expression in LUSQ. Including the morphometric parameters related to nuclear atypia in conjunction with PD-L1 status could help determine an effective ICI therapeutic strategy; however, further investigation is required.

Exploration of molecular markers related to chemotherapy efficacy of hepatoid adenocarcinoma of the stomach

PURPOSE

Preoperative neoadjuvant chemotherapy may not improve the prognosis of patients with hepatoid adenocarcinoma of the stomach (HAS), a rare pathological type of gastric cancer. Thus, the study aimed at the genomic and transcriptomic impacts of preoperative chemotherapy on HAS.

METHODS

Patients with HAS who underwent surgical resection at Peking University Cancer Hospital were retrospectively included in this study. Whole exome sequencing and transcriptome sequencing were performed on pre-chemotherapy, non-chemotherapy and post-chemotherapy samples. We then compared the alterations in molecular markers between the post-chemotherapy and non-chemotherapy groups, and between the chemotherapy-effective and chemotherapy-ineffective groups, respectively.

RESULTS

A total of 79 tumor samples from 72 patients were collected. Compared to the non-chemotherapy group, the mutation frequencies of several genes were changed after chemotherapy, including TP53. In addition, there was a significant increase in the frequency of frameshift mutations and cytosine transversion to adenine (C > A), appearance of COSMIC signature 6 and 14, and a reduced gene copy number amplification. Interestingly, the same phenomenon was observed in chemotherapy-ineffective patients. In addition, many HAS patients had ERBB2, FGFR2, MET and HGF gene amplification. Moreover, the expression of immune-related genes, especially those related to lymphocyte activation, was down-regulated after chemotherapy.

CONCLUSION

Chemotherapy is closely associated with changes in the molecular characteristics of HAS. After chemotherapy, at genomic and transcriptome level, many features were altered. These changes may be molecular markers of poor chemotherapeutic efficacy and play an important role in chemoresistance in HAS. In addition, ERBB2, FGFR2, MET and HGF gene amplification may be potential therapeutic targets for HAS.

DeepRisk network: an AI-based tool for digital pathology signature and treatment responsiveness of gastric cancer using whole-slide images

BACKGROUND

Digital histopathology provides valuable information for clinical decision-making. We hypothesized that a deep risk network (DeepRisk) based on digital pathology signature (DPS) derived from whole-slide images could improve the prognostic value of the tumor, node, and metastasis (TNM) staging system and offer chemotherapeutic benefits for gastric cancer (GC).

METHODS

DeepRisk is a multi-scale, attention-based learning model developed on 1120 GCs in the Zhongshan dataset and validated with two external datasets. Then, we assessed its association with prognosis and treatment response. The multi-omics analysis and multiplex Immunohistochemistry were conducted to evaluate the potential pathogenesis and spatial immune contexture underlying DPS.

RESULTS

Multivariate analysis indicated that the DPS was an independent prognosticator with a better C-index (0.84 for overall survival and 0.71 for disease-free survival). Patients with low-DPS after neoadjuvant chemotherapy responded favorably to treatment. Spatial analysis indicated that exhausted immune clusters and increased infiltration of CD11b+CD11c+ immune cells were present at the invasive margin of high-DPS group. Multi-omics data from the Cancer Genome Atlas-Stomach adenocarcinoma (TCGA-STAD) hint at the relevance of DPS to myeloid derived suppressor cells infiltration and immune suppression.

CONCLUSION

DeepRisk network is a reliable tool that enhances prognostic value of TNM staging and aid in precise treatment, providing insights into the underlying pathogenic mechanisms.

Genomic and transcriptomic analysis of breast cancer identifies novel signatures associated with response to neoadjuvant chemotherapy

BACKGROUND

Neoadjuvant chemotherapy (NAC) has become a standard treatment strategy for breast cancer (BC). However, owing to the high heterogeneity of these tumors, it is unclear which patient population most likely benefit from NAC. Multi-omics offer an improved approach to uncovering genomic and transcriptomic changes before and after NAC in BC and to identifying molecular features associated with NAC sensitivity.

METHODS

We performed whole-exome and RNA sequencing on 233 samples (including matched pre- and post-treatment tumors) from 50 BC patients with rigorously defined responses to NAC and analyzed changes in the multi-omics landscape. Molecular features associated with NAC response were identified and validated in a larger internal, and two external validation cohorts, as well as in vitro experiments.

RESULTS

The most frequently altered genes were TP53, TTN, and MUC16 in both pre- and post-treatment tumors. In comparison with pre-treatment tumors, there was a significant decrease in C > A transversion mutations in post-treatment tumors (P = 0.020). NAC significantly decreased the mutation rate (P = 0.006) of the DNA repair pathway and gene expression levels (FDR = 0.007) in this pathway. NAC also significantly changed the expression level of immune checkpoint genes and the abundance of tumor-infiltrating immune and stroma cells, including B cells, activated dendritic cells, γδT cells, M2 macrophages and endothelial cells. Furthermore, there was a higher rate of C > T substitutions in NAC nonresponsive tumors than responsive ones, especially when the substitution site was flanked by C and G. Importantly, there was a unique amplified region at 8p11.23 (containing ADGRA2 and ADRB3) and a deleted region at 3p13 (harboring FOXP1) in NAC nonresponsive and responsive tumors, respectively. Particularly, the CDKAL1 missense variant P409L (p.Pro409Leu, c.1226C > T) decreased BC cell sensitivity to docetaxel, and ADGRA2 or ADRB3 gene amplifications were associated with worse NAC response and poor prognosis in BC patients.

CONCLUSIONS

Our study has revealed genomic and transcriptomic landscape changes following NAC in BC, and identified novel biomarkers (CDKAL1P409L, ADGRA2 and ADRB3) underlying chemotherapy resistance and poor prognosis, which could guide the development of personalized treatments for BC.

Current status and perspectives of genetic testing in gastrointestinal cancer (Review)

Genetic testing has become widespread in daily medical care for gastrointestinal (GI) cancers. However, unlike breast cancer and non-small cell lung cancer, in which personalized medicine targeting various driver genes is standardized, the incidence of targeted gene abnormalities in GI cancers is low. Nevertheless, such abnormalities may be linked to therapeutic agents and the further development of therapeutic agents for personalized medicine for GI cancers is desired. A liquid biopsy is of great benefit in offering clinical decision support, in applications such as GI cancer screening, surgical interventions, monitoring disease status and enhancing patient survival outcomes, all of which would contribute to personalized medicine. Germline genetic testing is required for several types of GI cancer, which shows clinical indications of hereditary predisposition. The increasing use of multigene panel testing has redefined gene-cancer associations, and consequently the estimate of cancer risk that vary from low to high penetrance. Comprehensive genetic testing can enable the detection of novel treatment targets and the discovery of undefined multiple diagnostic/predictive markers, which may enhance the molecular-level understanding of GI cancers. Genetic testing can also aid the design of more appropriate and adequate genomic-driven therapies for patients who may benefit from other standardized therapeutic methods.

Value of spectral CT parameters in predicting the efficacy of neoadjuvant chemotherapy for gastric cancer

AIM

To investigate the value of pre-chemotherapy spectral computed tomography (CT) parameters in predicting neoadjuvant chemotherapy (NAC) response in gastric cancer (GC).

MATERIALS AND METHODS

Sixty patients with GC who received NAC and underwent spectral CT examination before chemotherapy were enrolled retrospectively and divided into a responsive group and a non-responsive group according to the postoperative pathological tumour regression grade. Clinical characteristics were collected. The iodine concentration (IC), water concentration (WC), and effective atomic number (Eff-Z) of the portal venous phases were measured before chemotherapy, and IC was normalised to that of the aorta to provide the normalised IC (NIC). An independent samples t-test, Mann-Whitney U-test, or chi-square test was used to analyse the differences between the two groups, and the receiver operating curve (ROC) was used to evaluate the predictive performance of different variables.

RESULTS

The neutrophil-to-lymphocyte ratio (NLR) was lower in the responsive group than in the non-responsive group (p<0.05). IC, NIC, and Eff-Z values were significantly higher in the responsive group than in the non-responsive group (p<0.01). The areas under the ROC curves for the NLR, IC, NIC, and Eff-Z were 0.694, 0.688, 0.799, and 0.690, respectively. The combination of NIC, Eff-Z, and NLR values showed good diagnostic performance in predicting response to NAC in GC, with an area under the ROC curve of 0.857, 76.92% sensitivity, 80% accuracy, and 85.71% specificity.

CONCLUSION

Spectral CT parameters may serve as non-invasive tools for predicting the response to NAC in patients with GC.

A novel prognostic and therapeutic target biomarker based on complement-related gene signature in gastric cancer

Background

Gastric cancer (GC) is one of the most prevalent cancer types that reduce human life expectancy. The current tumor-node-metastasis (TNM) staging system is inadequate in identifying higher or lower risk of GC patients because of tumor heterogeneity. Research shows that complement plays a dual role in the tumor development and progression of GC.

Methods

We downloaded GC data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). A complement-related risk signature was constructed through bioinformatics analysis. Subsequently, the predictive ability of this signature was validated with GSE84437 dataset, and a nomogram integrating risk score and common clinical factors was established. Besides, we evaluated the association of risk score with the immune and stromal cell infiltration in TCGA. Furthermore, immunotherapy response prediction and drug susceptibility analysis were conducted to access the ability of the risk signature in predicting the therapeutic effect.

Results

A complement-related gene (CRG) signature, based on six genes (SPLG, C9, ITIH1, ZFPM2, CD36, and SERPINE1), was established. In both the training and validation sets, the overall survival of GC patients in the high-risk group was lower than that of the low-risk group, and the nomogram to predict the 1-, 2-, and 3-year survival rates of GC patients was developed. In addition, CIBERSORT algorithm showed the high-risk patients had higher levels of immune cell infiltration than low-risk patients, and the ESTIMATE results implied that the high-risk group had more stromal component in tumor microenvironment. Besides, compared to the low-risk group, there were higher expressions of most immune checkpoint genes and HLA genes in the high-risk group, and the high-risk patients showed higher sensitivity to the chemotherapy and targeted drugs (axitinib, dasatinib, pazopanib, saracatinib, sunitinib and temsirolimus).

Conclusions

The novel CRG signature may act as a reliable, efficient tool for prognostic prediction and treatment guidance in future clinical practice.

Survival Outcomes and Patterns of Care for Stage II or III Resected Gastric Cancer by Race and Ethnicity

Importance

Many multimodality treatment regimens exist for gastric adenocarcinoma, including neoadjuvant vs adjuvant chemotherapy, radiation, or both. Neoadjuvant therapy is recommended in the United States for patients with locally advanced gastric cancer; however, it is unknown whether the outcomes of neoadjuvant therapy are associated with race and ethnicity.

Objective

To evaluate the differences in outcomes by race and ethnicity of patients with noncardia gastric cancer undergoing surgical procedures with and without neoadjuvant therapy.

Design, Setting, and Participants

This retrospective cohort study examined the National Cancer Database from the American College of Surgeons for patients with clinical stage II or III gastric adenocarcinoma, excluding gastric cardia tumors, undergoing surgical resection procedures from January 2006 to December 2019. Statistical analysis was performed from December 2021 to May 2023.

Exposure

Patients were stratified by race and ethnicity, and their outcomes were analyzed for those who received and did not receive neoadjuvant therapy.

Main Outcomes and Measures

The Cox proportional hazard model was used to compare overall survival (OS) between racial and ethnic groups (Asian, Black, Hispanic, and White) overall and according to receipt of neoadjuvant therapy. Among those who received neoadjuvant therapy, proportional differences in pathological responses were calculated in each group.

Results

Among a total of 6938 patients in the cohort, 4266 (61.4%) were male; mean (SD) age was 65.9 (12.8) years; 1046 (15.8%) were Asian, 1606 (24.3%) were Black, 1175 (17.8%) were Hispanic, and 3540 (53.6%) were White. Compared with other races and ethnicities, the group of White patients had significantly more who were 65 years or older with more comorbidities. White patients underwent surgical resection procedures alone without neoadjuvant or adjuvant therapy more frequently than other races and ethnicities. Asian and Black patients had the highest proportion of being downstaged or achieving pathological complete response after neoadjuvant therapy. In multivariate models, perioperative chemotherapy was associated with improved OS (HR, 0.79 [95% CI, 0.69-0.90]), whereas number of positive lymph nodes and surgical margins were associated with the largest decreases in OS. Asian and Hispanic race and ethnicity were associated with significantly improved OS compared with Black and White races (eg, Asian patients: HR, 0.64 [95% CI, 0.58-0.72]; and Hispanic patients: HR, 0.77 [95% CI, 0.69-0.85]). Black race was associated with improved OS compared with White race when receiving neoadjuvant therapy (HR, 0.78 [95% CI, 0.67-0.90]).

Conclusions and Relevance

In this large nationwide cohort study of survival outcomes among patients with resected clinical stage II or III gastric cancer, there were significant differences in response to treatment and OS between different racial and ethnic groups.

Role of microsatellite instability and HER2 positivity in locally advanced esophago-gastric cancer patients treated with peri-operative chemotherapy

PURPOSE

Neoadjuvant chemotherapy (NAC) significantly improved the prognosis of patients with locally advanced gastric cancer (LAGC). Several biomarkers, including HER2 and MMR/MSI are crucial for treatment decisions in the advanced stage but, currently, no biomarkers can guide the choice of NAC in clinical practice. Our aim was to evaluate the role of MSI and HER2 status on clinical outcomes.

METHODS

We retrospectively collected LAGC patients treated with NAC and surgery +/- adjuvant chemotherapy from 2006 to 2018. HER2 and MSI were assessed on endoscopic and surgical samples. Pathologic complete response (pCR) rate, overall survival (OS), and event-free survival (EFS) were estimated and evaluated for association with downstaging and MSI.

RESULTS

We included 76 patients, 8% were classified as MSI-H, entirely consistent between endoscopic and surgical samples. Six percent of patients were HER2 positive on endoscopic and 4% on surgical samples. Tumor downstaging was observed in 52.5% of cases, with three pCR (5.1%), none in MSI-H cancers. According to MSI status, event-free survival (EFS) and overall survival (OS) were higher for MSI-H patients to MSS [EFS not reached vs 30.0 months, p = 0.08; OS not reached vs 39.6 months, p = 0.10].

CONCLUSION

Our work confirms the positive prognostic effect of MSI-H in the curative setting of LAGC, not correlated with pathologic tumor downstaging. Prospective ad-hoc trial and tumor molecular profiling are eagerly needed.

Evolution of immune and stromal cell states and ecotypes during gastric adenocarcinoma progression

Understanding tumor microenvironment (TME) reprogramming in gastric adenocarcinoma (GAC) progression may uncover novel therapeutic targets. Here, we performed single-cell profiling of precancerous lesions, localized and metastatic GACs, identifying alterations in TME cell states and compositions as GAC progresses. Abundant IgA+ plasma cells exist in the premalignant microenvironment, whereas immunosuppressive myeloid and stromal subsets dominate late-stage GACs. We identified six TME ecotypes (EC1-6). EC1 is exclusive to blood, while EC4, EC5, and EC2 are highly enriched in uninvolved tissues, premalignant lesions, and metastases, respectively. EC3 and EC6, two distinct ecotypes in primary GACs, associate with histopathological and genomic characteristics, and survival outcomes. Extensive stromal remodeling occurs in GAC progression. High SDC2 expression in cancer-associated fibroblasts (CAFs) is linked to aggressive phenotypes and poor survival, and SDC2 overexpression in CAFs contributes to tumor growth. Our study provides a high-resolution GAC TME atlas and underscores potential targets for further investigation.

Using Normalized Carcinoembryonic Antigen and Carbohydrate Antigen 19 to Predict and Monitor the Efficacy of Neoadjuvant Chemotherapy in Locally Advanced Gastric Cancer

Carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA19-9) are established prognostic biomarkers for patients with gastric cancer. However, their potential as predictive markers for neoadjuvant chemotherapy (NACT) efficacy has not been fully elucidated.

METHODS

We conducted a retrospective analysis to determine values of CEA and CA19-9 prior to NACT (pre-NACT) and after NACT (post-NACT) in 399 patients with locally advanced gastric cancer (LAGC) who received intended NACT and surgery.

RESULTS

Among the 399 patients who underwent NACT plus surgery, 132 patients (33.1%) had elevated pre-NACT CEA/CA19-9 values. Furthermore, either pre-NACT or post-NACT CEA /CA19-9 levels were significantly associated with prognosis (p = 0.0023) compared to patients with non-elevated levels. Moreover, among the patients, a significant proportion (73/132, 55.3%) achieved normalized CEA/CA19-9 following NACT, which is a strong marker of a favorable treatment response and survival benefits. In addition, the patients with normalized CEA/CA19-9 also had a prolonged survival compared to those who underwent surgery first (p = 0.0140), which may be attributed to the clearance of micro-metastatic foci. Additionally, the magnitude of CEA/CA19-9 changes did not exhibit a statistically significant prognostic value.

CONCLUSIONS

Normalization of CEA/CA19-9 is a strong biomarker for the effectiveness of treatment, and can thus be exploited to prolong the long-term survival of patients with LAGC.

ADAR1-mediated RNA editing of SCD1 drives drug resistance and self-renewal in gastric cancer

Targetable drivers governing 5-fluorouracil and cisplatin (5FU + CDDP) resistance remain elusive due to the paucity of physiologically and therapeutically relevant models. Here, we establish 5FU + CDDP resistant intestinal subtype GC patient-derived organoid lines. JAK/STAT signaling and its downstream, adenosine deaminases acting on RNA 1 (ADAR1), are shown to be concomitantly upregulated in the resistant lines. ADAR1 confers chemoresistance and self-renewal in an RNA editing-dependent manner. WES coupled with RNA-seq identify enrichment of hyper-edited lipid metabolism genes in the resistant lines. Mechanistically, ADAR1-mediated A-to-I editing on 3'UTR of stearoyl-CoA desaturase (SCD1) increases binding of KH domain-containing, RNA-binding, signal transduction-associated 1 (KHDRBS1), thereby augmenting SCD1 mRNA stability. Consequently, SCD1 facilitates lipid droplet formation to alleviate chemotherapy-induced ER stress and enhances self-renewal through increasing β-catenin expression. Pharmacological inhibition of SCD1 abrogates chemoresistance and tumor-initiating cell frequency. Clinically, high proteomic level of ADAR1 and SCD1, or high SCD1 editing/ADAR1 mRNA signature score predicts a worse prognosis. Together, we unveil a potential target to circumvent chemoresistance.

Reshaping the Pancreatic Cancer Microenvironment at Different Stages with Chemotherapy

The dynamic tumor microenvironment, especially the immune microenvironment, during the natural progression and/or chemotherapy treatment is a critical frontier in understanding the effects of chemotherapy on pancreatic cancer. Non-stratified pancreatic cancer patients always receive chemotherapeutic strategies, including neoadjuvant chemotherapy and adjuvant chemotherapy, predominantly according to their physical conditions and different disease stages. An increasing number of studies demonstrate that the pancreatic cancer tumor microenvironment could be reshaped by chemotherapy, an outcome caused by immunogenic cell death, selection and/or education of preponderant tumor clones, adaptive gene mutations, and induction of cytokines/chemokines. These outcomes could in turn impact the efficacy of chemotherapy, making it range from synergetic to resistant and even tumor-promoting. Under chemotherapeutic impact, the metastatic micro-structures in the primary tumor may be built to leak tumor cells into the lymph or blood vasculature, and micro-metastatic/recurrent niches rich in immunosuppressive cells may be recruited by cytokines and chemokines, which provide housing conditions for these circling tumor cells. An in-depth understanding of how chemotherapy reshapes the tumor microenvironment may lead to new therapeutic strategies to block its adverse tumor-promoting effects and prolong survival. In this review, reshaped pancreatic cancer tumor microenvironments due to chemotherapy were reflected mainly in immune cells, pancreatic cancer cells, and cancer-associated fibroblast cells, quantitatively, functionally, and spatially. Additionally, small molecule kinases and immune checkpoints participating in this remodeling process caused by chemotherapy are suggested to be blocked reasonably to synergize with chemotherapy.

Pre-therapeutic molecular biomarkers of pathological response to neoadjuvant chemotherapy in gastric and esophago-gastric junction adenocarcinoma: A systematic review and meta-analysis

PURPOSE

Multimodal treatment is the standard of care in patients with locally advanced gastric cancer. Unfortunately, the response rate after neoadjuvant treatment remains limited. The ability to predict the response has a potential to improve patient outcomes by promoting a more individualized approach. We sought to describe the current state of research in pre-treatment molecular biomarkers of response to neoadjuvant therapy in gastric adenocarcinoma available for testing before the initiation of treatment and to perform a systematic review and meta-analysis in order to summarize and evaluate the potential methods.

METHODS

A systematic MEDLINE, EMBASE and CENTRAL literature search was conducted to extract articles on potentially predictive molecular biomarkers of pathological response to neoadjuvant therapy in patients with gastric- and esophago-gastric junction adenocarcinoma. Fixed and random effects models were used to undertake the meta-analysis when appropriate.

RESULTS

Data on predictive biomarkers was reported in 38 studies. These articles described 47 biomarkers showing statistical significance. After evaluation of all reported biomarkers, 3 of them met the inclusion criteria for meta-analysis. The meta-analysis results indicate that >5 ​ng/mL pre-therapeutic serum concentration of carcinoembryonic antigen (CEA; norm <5 ​ng/mL) is significantly associated with tumor response (RR ​= ​5.13, 95% CI 2.53-10.43, P ​= ​0.026).

CONCLUSION

Previous studies describe a large number of candidate biomarkers. Our meta-analysis indicated pre-therapeutic serum concentration of CEA >5 ​ng/mL as a potential and easy-accessible biomarker available for use before initiation of treatment. However, it could be only an additional tool for complex qualification for neoadjuvant therapy.

Multiplex immune profiling reveals the role of serum immune proteomics in predicting response to preoperative chemotherapy of gastric cancer

Responses toward preoperative chemotherapy are heterogeneous in patients with gastric adenocarcinoma. Existing studies in the field focus heavily on the tumor microenvironment (TME), whereas little is known about the relationship between systemic immunity and chemotherapy response. In this study, we collect serum samples from patients with gastric adenocarcinoma before, on, and after preoperative chemotherapy and study their immune proteomics using an antibody-based proteomics panel. We also collect surgically resected tumor samples and incorporate multiple methods to assess their TME. We find that both local and systemic immune features are associated with treatment response. Preoperative chemotherapy induces a sophisticated systemic immune response indicated by dynamic serum immune proteomics. A pretreatment serum protein scoring system is established for response prediction. Together, these findings highlight the fundamental but largely underestimated role of systemic immunity in the treatment of gastric cancer, suggesting a patient stratification strategy based on pretreatment serum immune proteomics.

Combining neoadjuvant chemotherapy with PD-1/PD-L1 inhibitors for locally advanced, resectable gastric or gastroesophageal junction adenocarcinoma: A systematic review and meta-analysis

Background

Immune checkpoint inhibitors (ICIs) have shown promising prospects in locally advanced, resectable gastric or gastroesophageal junction adenocarcinoma (GC/GEJC) immunotherapy, but their efficacy in neoadjuvant settings remains unclear. This study aimed to assess the efficacy and safety of integrating programmed cell death 1 (PD-1)/programmed cell death ligand 1 (PD-L1) inhibitors into neoadjuvant chemotherapy (NACT) of GC/GEJC treatment.

Methods

PubMed, Cochrane Library, Embase, ClinicalTrials.gov, and main oncology conference databases were systematically searched up to 19 November 2022, and randomized controlled trials (RCTs) and cohort studies that evaluated the efficacy and safety of PD-1/PD-L1 inhibitors plus NACT were included. The main outcomes were pathological complete response (pCR), major pathological response (MPR), R0 resection rate, and treatment-related adverse events (TRAEs).

Results

A total of 753 patients from 20 prospective studies were included in this meta-analysis. The pooled pCR and MPR rates from studies reporting were 21.7% [95% confidence interval (CI), 18.1%-25.5%] and 44.0% (95% CI, 34.1%-53.8%), respectively. The pooled incidence rate of total TRAEs was 89.1% (95% CI, 82.7%-94.3%), and the incidence rate of grade 3 to 4 TRAEs was 34.4% (95% CI, 17.8%-66.5%). The pooled R0 resection rate was reported to be 98.9% (95% CI, 97.0%-99.9%). Subgroup analysis has not found significant differences in efficacy and safety among different PD-1/PD-L1 inhibitors. Moreover, the efficacy in patients with positive PD-L1 expression (combined positive score ≥1) was comparable with that in the entire study population [pCR, 22.5% vs. 21.2% (p > 0.05); MPR, 48.6% vs. 43.7% (p > 0.05)].

Conclusion

This systematic review and meta-analysis found that PD-1/PD-L1 inhibitors combined with NACT for locally advanced GC/GEJC were well tolerated and may confer therapeutic advantages. The integration of ICIs into NACT has shown the potential for application in any PD-L1 expression population.

Interval time between neoadjuvant chemotherapy and surgery in advanced gastric cancer doesn't affect outcome: A meta analysis

Background

The efficacy of neoadjuvant chemotherapy for advanced gastric cancer is not yet firmly confirmed, but the exciting results demonstrated in several clinical studies have led neoadjuvant chemotherapy as the important treatment methods in guidelines. The 4-6 weeks interval time is currently the most commonly used in clinical treatment, but there are insufficient studies to support this time and the optimal interval has not yet been identified. The aim of this meta-analysis was to investigate the short-term life quality and long-term prognostic impact of the interval time between the end of neoadjuvant chemotherapy and surgery in patients with advanced gastric cancer.

Methods

We conducted a systematic literature search in PUBMED, Embase and Cochrane Liabrary for studies published or reported in English from January 2006 to May 2022. We summarised relevant studies for the time to surgery (TTS), included as retrospective studies and prospective studies. The primary study outcome was the rate of pathological complete response (pCR), and the secondary outcomes included R0 resection rate, incidence of serious postoperative complications, 3-year progression free survival time (PFS) rate and overall survival time (OS) rate. TTS were classified in three groups: 4-6 weeks, <4 weeks and >6 weeks. The ratio ratios (ORs) were calculated and forest plots and funnel plots were made to analysis by using fixed-effect and random-effect models in Review Manager 5.2.

Results

A total of five studies included 1,171 patients: 411 patients in shorter TTS group (<4 weeks), 507 patients in medium TTS group (4-6 weeks) and 253 patients in longer TTS groups (>6 weeks). And The results of our meta-analysis indicate that there are no significant difference between the three groups. The pCR, R0 resection rate, incidence of serious postoperative complications, 3-year PFS and OS were similar between three groups.

Conclusions

Although there many studies exploring the suitable TTS in advanced gastric cancer, but we have not find the evidence to prove the TTS is the risk factor influencing the outcome.

Systematic Review Registration

https://www.crd.york.ac.uk/PROSPERO/, identifier: CRD42022369009.

Neoadjuvant Chemotherapy in Asian Patients With Locally Advanced Gastric Cancer

Presently, surgery is the only treatment approach for gastric cancer and improving the prognosis of locally advanced gastric cancer is one of the key factors in promoting gastric cancer survival benefit. The MAGIC study was the first to demonstrate the efficacy of neoadjuvant chemotherapy (NAC) in European countries. In recent years, several clinical trials have provided evidence for the use of NAC in Asian patients with locally advanced gastric cancer. However, clinical practice guidelines vary between Asian and non-Asian populations. Optimal NAC regimens, proper target populations, and predictors of NAC outcomes in Asian patients are still under investigation. Herein, we summarized the current progress in the administration of NAC in Asian patients with gastric cancer.

A liquid biopsy signature of circulating exosome-derived mRNAs, miRNAs and lncRNAs predict therapeutic efficacy to neoadjuvant chemotherapy in patients with advanced gastric cancer

At present, there is no validated marker to identify the subpopulation of patients with advanced gastric cancer (AGC) who might benefit from neoadjuvant chemotherapy (NACT). In view of this clinical challenge, the identification of non-invasive biomarkers for efficacy prediction of NACT in patients with AGC is imperative. Herein, we aimed to develop a non-invasive, liquid-biopsy-based assay by using an exosome-derived RNAs model based on multi-omics characteristics of RNAs. We firstly used a multi-omics strategy to characterize the mRNAs, microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) profiles of circulating exosome enriched fractions in responders to NACT paired with non-responders, using RNA sequencing. Finally, numerous miRNAs, mRNAs and lncRNAs were identified to be associated with the response to NACT in patients with AGC, and it was validated in an independent cohort with promising AUC values. Furthermore, we established a 6-exosome-RNA panel that could robustly identified responders from non-responders treated with fluorouracil-based neoadjuvant chemotherapy.

Reconstruction of the gastric cancer microenvironment after neoadjuvant chemotherapy by longitudinal single-cell sequencing

BACKGROUND

Little is known on the tumor microenvironment (TME) response after neoadjuvant chemotherapy (NACT) in gastric cancer on the molecular level.

METHODS

Here, we profiled 33,589 cell transcriptomes in 14 samples from 11 gastric cancer patients (4 pre-treatment samples, 4 post-treatment samples and 3 pre-post pairs) using single-cell RNA sequencing (scRNA-seq) to generate the cell atlas. The ligand-receptor-based intercellular communication networks of the single cells were also characterized before and after NACT.

RESULTS

Compered to pre-treatment samples, CD4+ T cells (P = 0.018) and CD8+ T cells (P = 0.010) of post-treatment samples were significantly decreased, while endothelial cells and fibroblasts were increased (P = 0.034 and P = 0.005, respectively). No significant difference observed with respect to CD4+ Tregs cells, cycling T cells, B cells, plasma cells, macrophages, monocytes, dendritic cells, and mast cells (P > 0.05). In the unsupervised nonnegative matrix factorization (NMF) analysis, we revealed that there were three transcriptional programs (NMF1, NMF2 and NMF3) shared among these samples. Compared to pre-treatment samples, signature score of NMF1 was significantly downregulated after treatment (P = 0.009), while the NMF2 signature was significantly upregulated after treatment (P = 0.013). The downregulated NMF1 and upregulated NMF2 signatures were both associated with improved overall survival outcomes based on The Cancer Genome Atlas (TCGA) database. Additionally, proangiogenic pathways were activated in tumor and endothelial cells after treatment, indicating that NACT triggers vascular remodeling by cancer cells together with stromal cells.

CONCLUSIONS

In conclusion, our study provided transcriptional profiles of TME between pre-treatment and post-treatment for in-depth understanding on the mechanisms of NACT in gastric cancer and empowering the development of potential optimized therapy procedures and novel drugs.

The Regulatory Network of Gastric Cancer Pathogenesis and Its Potential Therapeutic Active Ingredients of Traditional Chinese Medicine Based on Bioinformatics, Molecular Docking, and Molecular Dynamics Simulation

Objective. This study aims to investigate the functional gene network in gastric carcinogenesis by using bioinformatics; besides, the diagnostic utility of key genes and potential active ingredients of traditional Chinese medicine (TCM) for treatment in gastric cancer have been explored. Methods. The Cancer Genome Atlas and Gene Expression Omnibus databases have been applied to analyze the differentially expressed genes (DEGs) between gastric cancer and normal gastric tissues. Then, the DEGs underwent Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses using the Metascape database. The STRING database and the Cytoscape software were utilized for the protein-protein interaction network of DEGs and hub genes screening. Furthermore, survival and expression analyses of hub genes were conducted using Gene Expression Profiling Interactive Analysis and Human Protein Atlas databases. By using the Comparative Toxicogenomics Database, the hub genes interconnected with active ingredients of TCM were analyzed to provide potential information for the treatment of gastric cancer. After the molecular docking of the active ingredients of TCM to specific hub gene receptor proteins, the molecular dynamics simulation GROMACS was applied to validate the conformation of the strongest binding ability in the molecular docking. Results. A total of 291 significant DEGs were found, from which 12 hub genes were screened out. Among these hub genes, the expressions of five hub genes including COL1A1, COL5A2, MMP12, SERPINE1, and VCAN were significantly correlated with the overall survival. Furthermore, four potential therapeutic active ingredients of TCM were acquired, including quercetin, resveratrol, emodin, and schizandrin B. In addition, the molecular docking results exhibited that the active ingredients of TCM formed stable binding with the hub gene targets. SERPINE1 (3UT3)-Emodin and COL1A1 (7DV6)-Quercetin were subjected to molecular dynamics simulations as conformations of continuing research significance, and both were found to be stably bound as a result of the interaction of van der Waals potentials, electrostatic, and hydrogen bonding. Conclusion. Our findings may provide novel insights and references for the screening of biomarkers, the prognostic evaluation, and the identification of potential active ingredients of TCM for gastric cancer treatment.

The effect of neoadjuvant chemotherapy on the tumor immune microenvironment in gastrointestinal tumors

In recent years, numerous studies have demonstrated that the tumor immune microenvironment (TIME) is capable of regulating the growth of tumors, and tumor-infiltrating immune cells in the TIME can affect the prognosis and treatment responses of patients. Consequently, therapies targeting these immune cells have emerged as important antitumor treatments. As a crucial componet of the perioperative treatment of malignant tumors, neoadjuvant chemotherapy (NACT) can improve the surgical resection rate and prognosis of patients and is a suitable clinical model to evaluate the effect of chemotherapy on the TIME. To provide a rationale for developing valid combinational therapies, this review summarizes the impact of NACT on the TIME, the relationship between tumor-infiltrating immune cells and treatment responses of patients, and the prognostic value of these infiltrating immune cells.

Clinical Significance and Immune Infiltration Analyses of the Cuproptosis-Related Human Copper Proteome in Gastric Cancer

BACKGROUND

The human copper Cu proteome, also termed Cu-binding proteins (CBP), is responsible for transporting "free" Cu to the cell that is related to cuproptosis. However, their role in gastric cancer (GC) has not been reported.

METHODS

RNA expression data of 946 GC patients were collected. A series of machine learning and bioinformatic approaches were combined to build a CBP signature to predict survival and immune microenvironment and guide the priority treatment. Immunohistochemistry and multicolor immunofluorescence (mIF) in 1076 resection slides were used to verify immune features.

RESULTS

A CBP signature was constructed using the machine learning method from TCGA that classifies cases as CBP_low and CBP_high groups. Multivariable Cox analysis confirmed that the CBP signature was an independent prognostic factor in the training and validation cohorts. Additionally, GC patients with low CBPscores showed an increase in anti-tumor immune microenvironment, which was further verified by mIF in pathological resections following immunotherapy. Importantly, patients with low CBPscores had higher levels of TMB/MSI and responded well to immunotherapy.

CONCLUSIONS

We conducted the first and comprehensive CBP analysis of GC patients and established a clinically feasible CBP signature for predicting survival and response to treatment, which will be helpful for guiding personalized medicine.

Upregulation of CRABP2 by TET1-mediated DNA hydroxymethylation attenuates mitochondrial apoptosis and promotes oxaliplatin resistance in gastric cancer

Oxaliplatin is the main chemotherapy drug for gastric cancer (GC), but quite a few patients are resistant to oxaliplatin, which contributes to the poor prognosis of GC patients. There is therefore an urgent need to identify potential targets for reversing chemotherapy resistance in GC patients. In this study, we analyzed the tumor samples of GC patients who received neoadjuvant chemotherapy based on oxaliplatin through quantitative proteomics and identified the potential chemoresistance-related protein cellular retinoic acid binding protein 2 (CRABP2). CRABP2 was significantly upregulated in the tumor tissues of chemoresistant GC patients and was closely related to prognosis. The results of cell function experiments showed that CRABP2 can promote the oxaliplatin resistance of GC cells in vitro. Coimmunoprecipitation and GST pulldown assays showed that CRAPB2 expedited the binding of BAX and PARKIN in GC cells and facilitated the ubiquitination-mediated degradation of BAX. Furthermore, both the in vitro assay and cell-derived xenograft (CDX) in vivo model verified that CRABP2 promoted oxaliplatin resistance by inhibiting BAX-dependent cell apoptosis. Further experiments proved that the abnormally high expression of CRABP2 in oxaliplatin-resistant GC cells was affected by TET1-mediated DNA hydroxymethylation. The patient-derived xenograft (PDX) model suggested that interference with CRABP2 reversed oxaliplatin resistance in GC in vivo. In conclusion, the results of our study show that CRABP2 was a key molecule in oxaliplatin resistance regulation and could be a new target for reversing the chemoresistance of GC.

Identification of a chemotherapy-associated gene signature for a risk model of prognosis in gastric adenocarcinoma through bioinformatics analysis

BACKGROUND

Over the past few years, the overall survival rate of patients with gastric adenocarcinoma who have received different chemotherapy regimens has increased. However, not all gastric cancer patients who receive chemotherapy have a longer survival. We need better predictive biomarkers. This study is to construct a new risk model of chemotherapy-associated genes in gastric adenocarcinoma (GA) for prognostication.

METHODS

RNA-seq data and clinical information of GSE26901 (containing 44 chemotherapy samples and 65 patients without chemotherapy) in Gene Expression Omnibus (GEO) and stomach adenocarcinoma (STAD, containing 360 cancer tissue samples and 50 paired normal tissue samples) in The Cancer Genome Atlas (TCGA) were selected for screening differentially expressed genes (DEGs). Multivariate Cox regression was conducted to screen prognosis-associated genes and its link to patients' prognosis were screened by least absolute shrinkage and selection operator (LASSO) regression analysis. Based on the key genes, a risk scoring equation for the prognosis model was established, and constructed survival prognosis model. The model was tested for predictive ability through training set (TCGA datasets) and validation set (GSE84437). The correlations of the risk score with clinical pathological features, immune score and drug sensitivity score were evaluated.

RESULTS

In total, 179 overlapping genes were obtained by screening DEGs. Univariate Cox analysis revealed 36 prognosis-related genes, and LASSO regression analysis revealed 8 key genes (KCNJ2, GATA5, CLDN1, SERPINE1, FCER2, PMEPA1, TMEM37 and CRTAC1). Kaplan-Meier (K-M) analysis uncovered a relatively short overall survival time in the high-risk group. The model was verified to possess favourable predictive ability. In addition, the nomogram model were demonstrated good predictability with area under the curve (AUC) for 1-5 years in training set were 0.78, 0.78, 0.76, 0.79 and 0.81. The high-risk group was less likely to get benefits from immunotherapy and less sensitive to cisplatin.

CONCLUSIONS

According to the results of our training set and validation set, the risk model based on the eight chemotherapy-related gene signatures predicting prognosis has certain predictive accuracy in predicting the survival of GA patients which can be a promising prognostic parameter for GA. However, its efficacy remains to be proved in clinical practice.

Applications of human organoids in the personalized treatment for digestive diseases

Digestive system diseases arise primarily through the interplay of genetic and environmental influences; there is an urgent need in elucidating the pathogenic mechanisms of these diseases and deploy personalized treatments. Traditional and long-established model systems rarely reproduce either tissue complexity or human physiology faithfully; these shortcomings underscore the need for better models. Organoids represent a promising research model, helping us gain a more profound understanding of the digestive organs; this model can also be used to provide patients with precise and individualized treatment and to build rapid in vitro test models for drug screening or gene/cell therapy, linking basic research with clinical treatment. Over the past few decades, the use of organoids has led to an advanced understanding of the composition of each digestive organ and has facilitated disease modeling, chemotherapy dose prediction, CRISPR-Cas9 genetic intervention, high-throughput drug screening, and identification of SARS-CoV-2 targets, pathogenic infection. However, the existing organoids of the digestive system mainly include the epithelial system. In order to reveal the pathogenic mechanism of digestive diseases, it is necessary to establish a completer and more physiological organoid model. Combining organoids and advanced techniques to test individualized treatments of different formulations is a promising approach that requires further exploration. This review highlights the advancements in the field of organoid technology from the perspectives of disease modeling and personalized therapy.

Berberine for gastric cancer prevention and treatment: Multi-step actions on the Correa's cascade underlie its therapeutic effects

Gastric carcinoma (GC) is a complex multifactorial disease occurring as sequential events commonly referred to as the Correa's cascade, a stepwise progression from non-active or chronic active gastritis, to gastric precancerous lesions, and finally, adenocarcinoma. Therefore, the identification of novel agents with multi-step actions on the Correa's cascade and those functioning as multiple phenotypic regulators are the future direction for drug discovery. Recently, berberine (BBR) has gained traction owing to its pharmacological properties, including anti-inflammatory, anti-cancer, anti-ulcer, antibacterial, and immunopotentiation activities. In this article, we investigated and summarized the multi-step actions of BBR on Correa's cascade and its underlying regulatory mechanism in gastric carcinogenesis for the first time, along with a discussion on the strength of BBR to prevent and treat GC. BBR was found to suppress H. pylori infection, control mucosal inflammation, and promote ulcer healing. In the gastric precancerous lesion phase, BBR could reverse mucosal atrophy and prevent lesions in intestinal metaplasia and dysplasia by regulating inflammatory cytokines, promoting cell apoptosis, regulating macrophage polarization, and regulating autophagy. Additionally, the therapeutic action of BBR on GC was partly realized through the inhibition of cell proliferation, migration, and angiogenesis; induction of apoptosis and autophagy, and enhancement of chemotherapeutic drug sensitivity. BBR exerted multi-step actions on the Correa's cascade, thereby halting and even reversing gastric carcinogenesis in some cases. Thus, BBR could be used to prevent and treat GC. In conclusion, the therapeutic strategy underlying BBR's multi-step action in the trilogy of Correa's cascade may include "prevention of gastric mucosal inflammation (Phase 1); reversal of gastric precancerous lesions (Phase 2), and rescue of GC (Phase 3)". The NF-κB, PI3K/Akt, and MAPK signaling pathways may be the key signaling transduction pathways underlying the treatment of gastric carcinogenesis using BBR. The advantage of BBR over conventional drugs is its multifaceted and long-term effects. This review is expected to provide preclinical evidence for using BBR to prevent gastric carcinogenesis and treat gastric cancer.

Molecular evolutionary process of advanced gastric cancer during sequential chemotherapy detected by circulating tumor DNA

BACKGROUND

Efficacy of conventional sequential chemotherapy paradigm for advanced gastric cancer (AGC) patients has largely plateaued. Dynamic molecular changes during and after sequential chemotherapy have not been fully delineated. We aimed to profile the molecular evolutionary process of AGC patients during sequential chemotherapy by next generation sequencing (NGS) of plasma circulating tumor DNA (ctDNA).

METHODS

A total of 30 chemo-naïve patients who were diagnosed with unresectable advanced or metastatic stomach adenocarcinoma were enrolled. All patients received sequential chemotherapy regimens following the clinical guideline. One hundred and eight serial peripheral blood samples were collected at baseline, radiographical assessment and disease progression. Plasma ctDNA was isolated and a customized NGS panel was used to detect the genomic features of ctDNA including single nucleotide variants (SNVs) and gene-level copy number variations (CNVs). KEGG pathway enrichment analysis was performed.

RESULTS

Platinum-based combination chemotherapy was administrated as first-line regimen. Objective response rate was 50% (15/30). Patients with higher baseline values of copy number instability (CNI), CNVs and variant allel frequency (VAF) were more sensitive to platinum-based first-line regimens. Tumor mutation burden (TMB), CNI and CNV burden at partial response and stable disease were significantly lower than those at baseline, where at progressive disease they recovered to baseline levels. Dynamic change of TMB (ΔTMB) was correlated with progression-free survival of first-line treatment. Fluctuating changes of SNVs and gene-level CNVs could be observed during sequential chemotherapy. Under the pressure of conventional chemotherapy, the number of novel gene-level CNVs were found to be higher than that of novel SNVs. Such novel molecular alterations could be enriched into multiple common oncologic signaling pathways, including EGFR tyrosine kinase inhibitor resistance and platinum drug resistance pathways, where their distributions were found to be highly heterogenous among patients. The impact of subsequent regimens, including paclitaxel-based and irinotecan-based regimens, on the molecular changes driven by first-line therapy was subtle.

CONCLUSION

Baseline and dynamic changes of genomic features of ctDNA could be biomarkers for predicting response of platinum-based first-line chemotherapy in AGC patients. After treatment with standard chemotherapy regimens, convergent oncologic pathway enrichment was identified, which is yet characterized by inter-patient heterogenous gene-level CNVs.

Machine learning models based on immunological genes to predict the response to neoadjuvant therapy in breast cancer patients

Breast cancer (BC) is the most common malignancy worldwide and neoadjuvant therapy (NAT) plays an important role in the treatment of patients with early BC. However, only a subset of BC patients can achieve pathological complete response (pCR) and benefit from NAT. It is therefore necessary to predict the responses to NAT. Although many models to predict the response to NAT based on gene expression determined by the microarray platform have been proposed, their applications in clinical practice are limited due to the data normalization methods during model building and the disadvantages of the microarray platform compared with the RNA-seq platform. In this study, we first reconfirmed the correlation between immune profiles and pCR in an RNA-seq dataset. Then, we employed multiple machine learning algorithms and a model stacking strategy to build an immunological gene based model (Ipredictor model) and an immunological gene and receptor status based model (ICpredictor model) in the RNA-seq dataset. The areas under the receiver operator characteristic curves for the Ipredictor model and ICpredictor models were 0.745 and 0.769 in an independent external test set based on the RNA-seq platform, and were 0.716 and 0.752 in another independent external test set based on the microarray platform. Furthermore, we found that the predictive score of the Ipredictor model was correlated with immune microenvironment and genomic aberration markers. These results demonstrated that the models can accurately predict the response to NAT for BC patients and will contribute to individualized therapy.

Comprehensive Review of Uterine Fibroids: Developmental Origin, Pathogenesis, and Treatment

Uterine fibroids are benign monoclonal neoplasms of the myometrium, representing the most common tumors in women worldwide. To date, no long-term or noninvasive treatment option exists for hormone-dependent uterine fibroids, due to the limited knowledge about the molecular mechanisms underlying the initiation and development of uterine fibroids. This paper comprehensively summarizes the recent research advances on uterine fibroids, focusing on risk factors, development origin, pathogenetic mechanisms, and treatment options. Additionally, we describe the current treatment interventions for uterine fibroids. Finally, future perspectives on uterine fibroids studies are summarized. Deeper mechanistic insights into tumor etiology and the complexity of uterine fibroids can contribute to the progress of newer targeted therapies.

A Radiomics Nomogram Integrated With Clinic-Radiological Features for Preoperative Prediction of DNA Mismatch Repair Deficiency in Gastric Adenocarcinoma

Purpose

To develop and validate a radiomics nomogram integrated with clinic-radiological features for preoperative prediction of DNA mismatch repair deficiency (dMMR) in gastric adenocarcinoma.

Materials and Methods

From March 2014 to August 2020, 161 patients with pathologically confirmed gastric adenocarcinoma were included from two centers (center 1 as the training and internal testing sets, n = 101; center 2 as the external testing sets, n = 60). All patients underwent preoperative contrast-enhanced computerized tomography (CT) examination. Radiomics features were extracted from portal-venous phase CT images. Max-relevance and min-redundancy (mRMR) and least absolute shrinkage and selection operator (LASSO) methods were used to select features, and then radiomics signature was constructed using logistic regression analysis. A radiomics nomogram was built incorporating the radiomics signature and independent clinical predictors. The model performance was assessed using receiver operating characteristic (ROC) curve analysis, calibration curve, and decision curve analysis (DCA).

Results

The radiomics signature, which was constructed using two selected features, was significantly associated with dMMR gastric adenocarcinoma in the training and internal testing sets (P < 0.05). The radiomics signature model showed a moderate discrimination ability with an area under the ROC curve (AUC) of 0.81 in the training set, which was confirmed with an AUC of 0.78 in the internal testing set. The radiomics nomogram consisting of the radiomics signature and clinical factors (age, sex, and location) showed excellent discrimination in the training, internal testing, and external testing sets with AUCs of 0.93, 0.82, and 0.83, respectively. Further, calibration curves and DCA analysis demonstrated good fit and clinical utility of the radiomics nomogram.

Conclusions

The radiomics nomogram combining radiomics signature and clinical characteristics (age, sex, and location) may be used to individually predict dMMR of gastric adenocarcinoma.

Multi-omics analysis reveals gut microbiota-induced intramuscular fat deposition via regulating expression of lipogenesis-associated genes

The gut microbiome has great effects on the digestion, absorption, and metabolism of lipids. However, the microbiota composition that can alter the fat deposition and the meat quality of pigs remains unclear. Here, we used Laiwu (LW) pigs (a native Chinese breed with higher intramuscular fat) compared with commercial crossbreed Duroc × (Landrace × Yorkshire) (DLY) pigs to investigate the effects of microbiota on meat quality, especially in intramuscular fat content. A total of 32 DLY piglets were randomly allotted to 4 groups and transplanted with fecal microbiota from healthy LW pigs. The results indicated that the high dose of fecal microbiota transplantation (HFMT) selectively enhanced fat deposition in longissimus dorsi (P < 0.05) but decreased backfat thickness (P < 0.05) compared with control group. HFMT significantly altered meat color and increased feed conversation ratio (P < 0.05). Furthermore, the multi-omics analysis revealed that Bacteroides uniformis, Sphaerochaeta globosa, Hydrogenoanaerobacterium saccharovorans, and Pyramidobacter piscolens are the core species which can regulate lipid deposition. A total of 140 male SPF C57BL/6j mice were randomly allotted into 7 groups and administrated with these 4 microbes alone or consortium to validate the relationships between microbiota and lipid deposition. Inoculating the bacterial consortium into mice increased intramuscular fat content (P < 0.05) compared with control mice. Increased expressions of lipogenesis-associated genes including cluster of differentiation 36 (Cd36), diacylglycerol O-acyltransferase 2 (Dgat2), and fatty acid synthase (FASN) were observed in skeletal muscle in the mice with mixed bacteria compared with control mice. Together, our results suggest that the gut microbiota may play an important role in regulating the lipid deposition in the muscle of pigs and mice.

Focal Adhesion-Related Signatures Predict the Treatment Efficacy of Chemotherapy and Prognosis in Patients with Gastric Cancer

Background

The current tumor-node-metastasis (TNM) staging system is insufficient for predicting the efficacy of chemotherapy in patients with gastric cancer (GC). This study aimed to analyze the association between the focal adhesion pathway and therapeutic efficacy of chemotherapy in patients with GC.

Methods

RNA sequencing was performed on 33 clinical samples from patients who responded or did not respond to treatment prior to neoadjuvant chemotherapy. The validation sets containing 696 GC patients with RNA data from three cohorts (PKUCH, TCGA, and GSE14210) were analyzed. A series of machine learning and bioinformatics approaches was combined to build a focal adhesion-related signature model to predict the treatment efficacy and prognosis of patients with GC.

Results

Among the various signaling pathways associated with cancer, focal adhesion was identified as a risk factor related to the treatment efficacy of chemotherapy and prognosis in patients with GC. The focal adhesion-related gene model (FAscore) discriminated patients with a high FAscore who are insensitive to neoadjuvant chemotherapy in our training cohort, and the predicted value was further verified in the GSE14210 cohort. Survival analysis also demonstrated that patients with high FAscores had a relatively shorter survival compared to those with low FAscores. In addition, we found that the levels of tumor mutation burden (TMB) and microsatellite instability (MSI) increased with an increase in FAscore, and the tumor microenvironment (TME) also shifted to a pro-tumor immune microenvironment.

Conclusion

The FAscore model can be used to predict the treatment efficacy of chemotherapy and select appropriate treatment strategies for patients with GC.

Deep Learning-Based Protein Features Predict Overall Survival and Chemotherapy Benefit in Gastric Cancer

Gastric cancer (GC) is one of the most common malignant tumors with a high mortality rate worldwide and lacks effective methods for prognosis prediction. Postoperative adjuvant chemotherapy is the first-line treatment for advanced gastric cancer, but only a subgroup of patients benefits from it. Here, we used 833 formalin-fixed, paraffin-embedded resected tumor samples from patients with TNM stage II/III GC and established a proteomic subtyping workflow using 100 deep-learned features. Two proteomic subtypes (S-I and S-II) with overall survival differences were identified. S-I has a better survival rate and is sensitive to chemotherapy. Patients in the S-I who received adjuvant chemotherapy had a significant improvement in the 5-year overall survival rate compared with patients who received surgery alone (65.3% vs 52.6%; log-rank P = 0.014), but no improvement was observed in the S-II (54% vs 51%; log-rank P = 0.96). These results were verified in an independent validation set. Furthermore, we also evaluated the superiority and scalability of the deep learning-based workflow in cancer molecular subtyping, exhibiting its great utility and potential in prognosis prediction and therapeutic decision-making.

Characterization of Tumor Mutation Burden-Based Gene Signature and Molecular Subtypes to Assist Precision Treatment in Gastric Cancer

Objective

Tumor mutation burden (TMB) represents a useful biomarker for predicting survival outcomes and immunotherapy response. Here, we aimed to conduct TMB-based gene signature and molecular subtypes in gastric cancer.

Methods

Based on differentially expressed genes (DEGs) between high- and low-TMB groups in TCGA, a LASSO model was developed for predicting overall survival (OS) and disease-free survival (DFS). The predictive performance was externally verified in the GSE84437 dataset. Molecular subtypes were conducted via consensus clustering approach based on TMB-related DEGs. The immune microenvironment was estimated by ESTIMATE and ssGSEA algorithms.

Results

High-TMB patients had prolonged survival duration. TMB-related DEGs were distinctly enriched in cancer- (MAPK, P53, PI3K-Akt, and Wnt pathways) and immune-related pathways (T cell selection and differentiation). The TMB-based gene model was developed (including MATN3, UPK1B, GPX3, and RGS2), and high-risk score was predictive of poor prognosis and recurrence. ROC and multivariate analyses revealed the well predictive performance, which was confirmed in the external cohort. Furthermore, we established the nomogram containing the risk score, age, and stage for personalized prediction of OS and DFS. High-risk score was characterized by high stromal score, increased immune checkpoints, immune cell infiltrations, and enhanced sensitivity to gefitinib, vinorelbine, and gemcitabine. Three TMB-based molecular subtypes were conducted, characterized by distinct prognosis, immune microenvironment, and drug sensitivity.

Conclusion

Collectively, we established a prognostic signature and three distinct molecular subtypes based on TMB features for gastric cancer, which might be beneficial for prognostic prediction and clinical decision-making.

Adjuvant Chemotherapy in pT2N0M0 Gastric Cancer: Findings From a Retrospective Study

Background: There is no global consensus on adjuvant chemotherapy (ACT) for pT2N0M0 gastric cancer. We conducted a retrospective study to reveal the role of ACT in such patients.

Methods: Patients with pT2N0M0 gastric cancer who underwent radical resection with D2 lymphadenectomy for primary gastric cancer between January 2012 and May 2016 were included. Kaplan–Meier and Cox regression were used to evaluate overall survival (OS), disease-specific survival (DSS) and predictors of prognosis. Stratified analysis based on high-risk factors was conducted.

Results: Of enrolled 307 patients, 111 patients underwent surgery alone and 196 patients received ACT. Surgery alone (HR = 2.913, 95% CI: 1.494-5.682, p = 0.002) and total gastrectomy (HR = 2.445, 95% CI: 1.279-4.675, p = 0.007) were independently associated with decreased OS. With the median follow-up of 73.1 months, the 5-year OS rate was 87.9% and 5-year DSS rate was 91.8%. Patients receiving ACT showed a better 5-year OS rate (92.9 vs. 79.3%, p < 0.001) and DSS rate (96.8 vs. 83.0%, p < 0.001) than patients underwent surgery alone. Patients receiving monotherapy (n = 130) had a relatively poor prognosis compared to patients receiving dual-drug (n = 66) without a significant difference (92.3 vs. 93.9%, p = 0.637). In patients without high-risk factors based on the Chinese Society of Clinical Oncology (CSCO) Guidelines, ACT also provided survival benefit (96.0 vs 82.9%, p = 0.038).

Conclusions: ACT was accompanied with higher 5-year OS and DSS rates of patients with pT2N0M0 gastric cancer. Patients with pT2N0M0 gastric cancer, regardless of high-risk factors based on the CSCO guidelines, might be considered candidates for ACT. In regard to the therapy regimen, monotherapy might be the optimal choice, considering the adverse events.

Mapping the genomic diaspora of gastric cancer

Gastric cancer (GC) is a leading contributor to global cancer incidence and mortality. Pioneering genomic studies, focusing largely on primary GCs, revealed driver alterations in genes such as ERBB2, FGFR2, TP53 and ARID1A as well as multiple molecular subtypes. However, clinical efforts targeting these alterations have produced variable results, hampered by complex co-alteration patterns in molecular profiles and intra-patient genomic heterogeneity. In this Review, we highlight foundational and translational advances in dissecting the genomic cartography of GC, including non-coding variants, epigenomic aberrations and transcriptomic alterations, and describe how these alterations interplay with environmental influences, germline factors and the tumour microenvironment. Mapping of these alterations over the GC life cycle in normal gastric tissues, metaplasia, primary carcinoma and distant metastasis will improve our understanding of biological mechanisms driving GC development and promoting cancer hallmarks. On the translational front, integrative genomic approaches are identifying diverse mechanisms of GC therapy resistance and emerging preclinical targets, enabled by technologies such as single-cell sequencing and liquid biopsies. Validating these insights will require specifically designed GC cohorts, converging multi-modal genomic data with longitudinal data on therapeutic challenges and patient outcomes. Genomic findings from these studies will facilitate 'next-generation' clinical initiatives in GC precision oncology and prevention.

Novel prognostic marker LINC00205 promotes tumorigenesis and metastasis by competitively suppressing miRNA-26a in gastric cancer

Rapid proliferation and metastasis of gastric cancer (GC) resulted in a poor prognosis in the clinic. Previous studies elucidated that long non-coding RNA (LncRNA) LINC00205 was upregulated in various tumors and participated in tumor progression. The aim of our study was to investigate the regulating role of LINC00205 in tumorigenesis and metastasis of GC. Both public datasets and our data showed that the LINC00205 was highly expressed in GC tissues and several cell lines. Notably, GC patients with high level of LINC00205 had a poor prognosis in our cohort. Mechanistically, knockdown of LINC00205 by shRNAs suppressed GC cells proliferation, migration, invasion remarkably, and induced cell cycle arrest. Based on bioinformatics prediction, we found that LINC00205 might act as a competitive endogenous RNA (ceRNA) through targeting miR-26a. The level of miR-26a had negatively correlated with LINC00205 expression and was decreased among GC cell lines, tissues, and serum samples. Our results for the first time confirmed that miR-26a was a direct target of LINC00205 and might have the potential to become a plasma marker for clinical tumor diagnosis. Indeed, LINC00205 knockdown resulted in the dramatic promotion of miR-26a expression as well as inhibition of miR-26a potential downstream targets, such as HMGA2, EZH2, and USP15. These targets were essential for cell survival and epithelial-mesenchymal transition. Importantly, LINC00205 was able to remodel the miR-26a-mediated downstream silence, which identified a new mechanism of malignant transformation of GC cells. In conclusion, this study revealed the regulating role of the LINC00205/miR-26a axis in GC progression and provided a new potential therapeutic strategy for GC treatment.

Novel Biomarkers of Gastric Adenocarcinoma: Current Research and Future Perspectives

Simple Summary

Gastric cancer is characterized by poor survival rates despite surgery and chemotherapy. Current research focuses on biomarkers to improve diagnosis and prognosis, and to enable targeted treatment strategies. The aim of our review was to give an overview over the wide range of novel biomarkers in gastric cancer. These biomarkers are targets of a specific treatment, such as antibodies against human epidermal growth factor receptor 2. Other promising biomarkers for targeted therapies that have shown relevance in clinical trials are vascular endothelial growth factor, programmed cell death protein 1, and Claudin 18.2. There is a vast number of biomarkers based on DNA, RNA, and protein expression, as well as detection of circulating tumor cells and the immune tumor microenvironment.

Abstract

Overall survival of gastric cancer remains low, as patients are often diagnosed with advanced stage disease. In this review, we give an overview of current research on biomarkers in gastric cancer and their implementation in treatment strategies. The HER2-targeting trastuzumab is the first molecular targeted agent approved for gastric cancer treatment. Other promising biomarkers for targeted therapies that have shown relevance in clinical trials are VEGF and Claudin 18.2. Expression of MET has been shown to be a negative prognostic factor in gastric cancer. Targeting the PD-1/PD-L1 pathway with immune checkpoint inhibitors has proven efficacy in advanced gastric cancer. Recent technology advances allow the detection of circulating tumor cells that may be used as diagnostic and prognostic indicators and for therapy monitoring in gastric cancer patients. Prognostic molecular subtypes of gastric cancer have been identified using genomic data. In addition, transcriptome profiling has allowed a comprehensive characterization of the immune and stromal microenvironment in gastric cancer and development of novel risk scores. These prognostic and predictive markers highlight the rapidly evolving field of research in gastric cancer, promising improved treatment stratification and identification of molecular targets for individualized treatment in gastric cancer.

Tumor mutation burden is correlated with response and prognosis in microsatellite-stable (MSS) gastric cancer patients undergoing neoadjuvant chemotherapy

BACKGROUND

Neoadjuvant chemotherapy (NACT) before radical gastrectomy is preferred for locally advanced gastric cancer (GC). However, clinical practices demonstrate that a considerable proportion of GC patients do not benefit from NACT, largely due to the lack of biomarkers for patient selection and prognosis prediction. A recent study revealed that patients with microsatellite instability-high (MSI-H) may be resistant to NACT, however, most tumors in Chinese GC patients (~ 95%) are characterized by microsatellite stability (MSS). Here, we aimed to discover new molecular biomarkers for this larger population.

METHODS

We performed whole-exome sequencing on 46 clinical samples (pre- and post-treatment) from 30 stage II/III MSS GC patients whose response to NACT was rigorously defined. Serum tumor markers (TMs), including AFP, CEA, CA199, CA724 and CA242 were measured during the course.

RESULTS

High tumor mutation burden (TMB-H) and 19q12 amplification (19q12 +) were positively associated with the NACT response. When TMB and 19q12 amplification were jointly analyzed, those with TMB-H or 19q12 + showed favorable response to NACT (p = 0.035). Further, TMB-H was negatively correlated with ypN stage, lymph node metastasis, and macrophage infiltration. Patients with TMB-H showed better disease-free survival (DFS) than those with TMB-L (P = 0.025, HR = 0.1331), and this was further validated using two larger GC datasets: TCGA-STAD (p = 0.004) and ICGC-CN (p = 0.045).

CONCLUSION

The combination of TMB-H and 19q12 + can serve as an early indicator of response to NACT. Superior to traditional clinical indicators, TMB-H is a robust and easily accessible candidate biomarker associated with better DFS, and can be evaluated at the time of diagnosis.

Machine Learning for Future Subtyping of the Tumor Microenvironment of Gastro-Esophageal Adenocarcinomas

Tumor progression involves an intricate interplay between malignant cells and their surrounding tumor microenvironment (TME) at specific sites. The TME is dynamic and is composed of stromal, parenchymal, and immune cells, which mediate cancer progression and therapy resistance. Evidence from preclinical and clinical studies revealed that TME targeting and reprogramming can be a promising approach to achieve anti-tumor effects in several cancers, including in GEA. Thus, it is of great interest to use modern technology to understand the relevant components of programming the TME. Here, we discuss the approach of machine learning, which recently gained increasing interest recently because of its ability to measure tumor parameters at the cellular level, reveal global features of relevance, and generate prognostic models. In this review, we discuss the relevant stromal composition of the TME in GEAs and discuss how they could be integrated. We also review the current progress in the application of machine learning in different medical disciplines that are relevant for the management and study of GEA.

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.

Predictive biomarkers for 5-fluorouracil and oxaliplatin-based chemotherapy in gastric cancers via profiling of patient-derived xenografts

Gastric cancer (GC) is commonly treated by chemotherapy using 5-fluorouracil (5-FU) derivatives and platinum combination, but predictive biomarker remains lacking. We develop patient-derived xenografts (PDXs) from 31 GC patients and treat with a combination of 5-FU and oxaliplatin, to determine biomarkers associated with responsiveness. When the PDXs are defined as either responders or non-responders according to tumor volume change after treatment, the responsiveness of PDXs is significantly consistent with the respective clinical outcomes of the patients. An integrative genomic and transcriptomic analysis of PDXs reveals that pathways associated with cell-to-cell and cell-to-extracellular matrix interactions enriched among the non-responders in both cancer cells and the tumor microenvironment (TME). We develop a 30-gene prediction model to determine the responsiveness to 5-FU and oxaliplatin-based chemotherapy and confirm the significant poor survival outcomes among cases classified as non-responder-like in three independent GC cohorts. Our study may inform clinical decision-making when designing treatment strategies.

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.

Geospatial Assessments of DNA Adducts in the Human Stomach: A Model of Field Cancerization

BACKGROUND

Field cancerization is a popular concept regarding where cancer cells arise in a plane, such as the opened-up gastrointestinal mucosa. The geospatial distribution of DNA adducts, some of which are believed to initiate mutation, may be a clue to understanding the landscape of the preferred occurrence of gastric cancer in the human stomach, such that the occurrence is much more frequent in the lesser curvature than in the greater curvature.

METHODS

Seven DNA adducts, C5-methyl-2'-deoxycytidine, 2'-deoxyinosine, C5-hydroxymethyl-2'-deoxycytidine, N6-methyl-2'-deoxyadenosine, 1,N6-etheno-2'-deoxyadenosine, N6-hydroxymethyl-2'-deoxyadenosine, and C8-oxo-2'-deoxyguanosine, from different points and zones of the human stomach were semi quantitatively measured by liquid chromatography/tandem mass spectrometry. The differences in the quantity of these DNA adducts from the lesser and greater curvature, the upper, middle and lower third zones, the anterior and posterior wall of the stomach, and the mucosae distant from and near the tumor were compared to determine whether the location preference of cancer in the stomach could be explained by the distribution of these DNA adducts. Comparisons were conducted considering the tumor locations and operation methods.

CONCLUSIONS

Regarding the DNA adducts investigated, significant differences in quantities and locations in the whole stomach were not noted; thus, these DNA adducts do not explain the preferential occurrence of cancer in particular locations of the human stomach.

Extracellular Matrix-Related Hubs Genes Have Adverse Effects on Gastric Adenocarcinoma Prognosis Based on Bioinformatics Analysis

Gastric adenocarcinoma (GAC) is the most frequent type of stomach cancer, characterized by high heterogeneity and phenotypic diversity. Although many novel strategies have been developed for treating GAC, recurrence and metastasis rates are still high. Therefore, it is necessary to screen new potential biomarkers correlated with prognosis and novel molecular targets. Gene expression profiles were obtained from the from NCBI Gene Expression Omnibus (GEO) database. We conduct an integrated analysis using the online Venny website to explore candidate hub genes between differentially expressed genes (DEGs) of two datasets. Gene ontology (GO) and Kyoto Encyclopedia 18 of Genes and Genomes (KEGG) pathway enrichment analysis found that extracellular matrix plays an important role in GAC. In addition, we applied protein-protein interaction (PPI) network analysis by using the Search Tool for the Retrieval of Interacting Genes (STRING) and visualized with Cytoscape software. Furthermore, we employed Cytoscape software to analyze the interactive relationship of candidate gene for further analysis. We found that ECM related proteins played an important role in GAC, and 15 hub genes were extracted from 123 DEGs genes. There were four hub genes (bgn, vcan, col1a1 and timp1) predicted to be associated with poor prognosis among the 15 hub genes.

Genomic Analysis of Response to Neoadjuvant Chemotherapy in Esophageal Adenocarcinoma

Neoadjuvant therapy followed by surgery is the standard of care for locally advanced esophageal adenocarcinoma (EAC). Unfortunately, response to neoadjuvant chemotherapy (NAC) is poor (20-37%), as is the overall survival benefit at five years (9%). The EAC genome is complex and heterogeneous between patients, and it is not yet understood whether specific mutational patterns may result in chemotherapy sensitivity or resistance. To identify associations between genomic events and response to NAC in EAC, a comparative genomic analysis was performed in 65 patients with extensive clinical and pathological annotation using whole-genome sequencing (WGS). We defined response using Mandard Tumor Regression Grade (TRG), with responders classified as TRG1-2 (n = 27) and non-responders classified as TRG4-5 (n =38). We report a higher non-synonymous mutation burden in responders (median 2.08/Mb vs. 1.70/Mb, p = 0.036) and elevated copy number variation in non-responders (282 vs. 136/patient, p < 0.001). We identified copy number variants unique to each group in our cohort, with cell cycle (CDKN2A, CCND1), c-Myc (MYC), RTK/PIK3 (KRAS, EGFR) and gastrointestinal differentiation (GATA6) pathway genes being specifically altered in non-responders. Of note, NAV3 mutations were exclusively present in the non-responder group with a frequency of 22%. Thus, lower mutation burden, higher chromosomal instability and specific copy number alterations are associated with resistance to NAC.