Gastric Cancer with Radiographically Occult Metastatic Disease: Biology, Challenges, and Diagnostic Approaches

Applications of Multimodal Artificial Intelligence in Non-Hodgkin Lymphoma B Cells

Given advancements in large-scale data and AI, integrating multimodal artificial intelligence into cancer research can enhance our understanding of tumor behavior by simultaneously processing diverse biomedical data types. In this review, we explore the potential of multimodal AI in comprehending B-cell non-Hodgkin lymphomas (B-NHLs). B-cell non-Hodgkin lymphomas (B-NHLs) represent a particular challenge in oncology due to tumor heterogeneity and the intricate ecosystem in which tumors develop. These complexities complicate diagnosis, prognosis, and therapy response, emphasizing the need to use sophisticated approaches to enhance personalized treatment strategies for better patient outcomes. Therefore, multimodal AI can be leveraged to synthesize critical information from available biomedical data such as clinical record, imaging, pathology and omics data, to picture the whole tumor. In this review, we first define various types of modalities, multimodal AI frameworks, and several applications in precision medicine. Then, we provide several examples of its usage in B-NHLs, for analyzing the complexity of the ecosystem, identifying immune biomarkers, optimizing therapy strategy, and its clinical applications. Lastly, we address the limitations and future directions of multimodal AI, highlighting the need to overcome these challenges for better clinical practice and application in healthcare.

Systematic review of diagnostic tools for peritoneal metastasis in gastric cancer-staging laparoscopy and its alternatives

BACKGROUND

Gastric cancer is one of the leading causes of cancer burden and mortality, often resulting in peritoneal metastasis in advanced stages with negative survival outcomes. Staging laparoscopy has become standard practice for suspected cases before a definitive gastrectomy or palliation. This systematic review aims to compare the efficacy of other diagnostic modalities instead of staging laparoscopy as the alternatives are able to reduce cost and invasive staging procedures. Recently, a radiomic model based on computed tomography and positron emission tomography (PET) has also emerged as another method to predict peritoneal metastasis.

AIM

To determine if the efficacy of computed tomography, magnetic resonance imaging and PET is comparable with staging laparoscopy.

METHODS

Articles comparing computed tomography, PET, magnetic resonance imaging, and radiomic models based on computed tomography and PET to staging laparoscopies were filtered out from the Cochrane Library, EMBASE, PubMed, Web of Science, and Reference Citations Analysis (https://www.referencecitationanalysis.com/). In the search for studies comparing computed tomography (CT) to staging laparoscopy, five retrospective studies and three prospective studies were found. Similarly, five retrospective studies and two prospective studies were also included for papers comparing CT to PET scans. Only one retrospective study and one prospective study were found to be suitable for papers comparing CT to magnetic resonance imaging scans.

RESULTS

Staging laparoscopy outperformed computed tomography in all measured aspects, namely sensitivity, specificity, positive predictive value and negative predictive value. Magnetic resonance imaging and PET produced mixed results, with the former shown to be only marginally better than computed tomography. CT performed slightly better than PET in most measured domains, except in specificity and true negative rates. We speculate that this may be due to the limited F-fluorodeoxyglucose uptake in small peritoneal metastases and in linitis plastica. Radiomic modelling, in its current state, shows promise as an alternative for predicting peritoneal metastases. With further research, deep learning and radiomic modelling can be refined and potentially applied as a preoperative diagnostic tool to reduce the need for invasive staging laparoscopy.

CONCLUSION

Staging laparoscopy was superior in all measured aspects. However, associated risks and costs must be considered. Refinements in radiomic modelling are necessary to establish it as a reliable screening technique.

Hsa_circ_0002019 promotes cell proliferation, migration, and invasion by regulating TNFAIP6/NF-κB signaling in gastric cancer

BACKGROUND

Gastric cancer (GC) is a common cancer with a high incidence and mortality rate. Herein, the role of hsa_circ_0002019 (circ_0002019) in GC was investigated.

METHODS

The molecular structure and stability of circ_0002019 were identified by RNase R, and Actinomycin D treatment. Molecular associations were verified by RIP. Proliferation, migration, and invasion were detected by CCK-8, EdU, and Transwell, respectively. The effect of circ_0002019 on tumor growth was analyzed in vivo.

RESULTS

Circ_0002019 was elevated in GC tissues and cells. Circ_0002019 knockdown inhibited the proliferation, migration, and invasion. Mechanically, circ_0002019 activated NF-κB signaling by increasing TNFAIP6 mRNA stability by PTBP1. Activation of NF-κB signaling limited the antitumor effect of circ_0002019 silencing in GC. Circ_0002019 knockdown inhibited tumor growth in vivo by reducing TNFAIP6 expression.

CONCLUSIONS

Circ_0002019 accelerated the proliferation, migration, and invasion by regulating TNFAIP6/NF-κB pathway, suggesting circ_0002019 could be a key regulatory factor in GC progression.

Lymph Node Involvement in Advanced Gastric Cancer in the Era of Multimodal Treatment-Oncological and Surgical Perspective

Simple Summary

Gastric cancer (GC) continues to be one of the major oncological challenges on a global scale. The role of neoadjuvant chemotherapy (NAC) in GC is to downstage primary tumour, eliminate potential micrometastases, and increase the chance for radical resection. Although systemic treatment prolongs the survival in advanced GC, persistent lymph node (LN) metastases indicate poor prognosis. Therefore, further identification of prognostic factors after NAC is urgent and could positively influence clinical outcomes. This article aimed to review the actual trends and future perspectives in multimodal therapy of advanced GC, with a particular interest in the post-neoadjuvant pathological nodal stage. Since downstaged and primarily node-negative patients show a similar prognosis, the main target for NAC in advanced GC should be nodal clearance. Adequate staging and personalised perioperative therapy seem to be of great importance in the multimodal treatment of GC.

Abstract

Gastric cancer (GC) continues to be one of the major oncological challenges on a global scale. The role of neoadjuvant chemotherapy (NAC) in GC is to downstage primary tumour, eliminate potential micrometastases, and increase the chance for radical resection. Although systemic treatment prolongs the survival in advanced GC, persistent lymph node (LN) metastases indicate poor prognosis. Further identification of prognostic factors after NAC is urgent and could positively influence clinical outcomes. This article aimed to review the actual trends and future perspectives in multimodal therapy of advanced GC, with a particular interest in the post-neoadjuvant pathological nodal stage. A favourable prognostic impact for ypN0 patients is observed, either due to truly negative LN before the start of therapy or because preoperative therapy achieved a pathologically complete nodal response. Ongoing trials investigating the extent of lymphadenectomy after neoadjuvant therapy will standardise the LN dissection from the multimodal therapy perspective. Since downstaged and primarily node-negative patients show a similar prognosis, the main target for NAC in advanced GC should be nodal clearance. Adequate staging and personalised perioperative therapy seem to be of great importance in the multimodal treatment of GC.