A clinical model in which key features of the tumor microenvironment are assessed was capable of accurately predicting which patients with early gastric cancer (EGC) had lymph node metastasis (LNM) and which did not, thus determining the optimal treatment course for patients, a retrospective study has suggested.
In an overall cohort of 375 patients with a T1 gastric cancer diagnosis, the depth of tumor invasion, tumor differentiation, and the collagen signature of the tumor microenvironment — deduced by multiphoton imaging — was able to accurately identify 92.1% of patients with LNM and had a negative predictive value of 96.9%, Jun Yan, MD, PhD, of Southern Medical University in Guangzhou, People’s Republic of China, and colleagues reported in JAMA Surgery.
The same model had a positive predictive value of 72.1%, a sensitivity of 87.3%, and a specificity of 97.1%, the researchers added. “Accurate assessment of the nodal status in EGC is important in the decision making for lymph node dissection.”
“With the assistance of the prediction model, EGC with a genuine high risk of LNM would be distinguished, and more tailored surgical interventions could be performed,” the team said.
The primary cohort consisted of 232 patients who underwent radical gastrectomy, although not neoadjuvant radiotherapy, chemotherapy, or chemoradiotherapy.
Two independent pathologists blinded to the nodal status of the patient evaluated the region of the invasive margin of the cancer and carried out multiphoton imaging to characterize the collagen features of each tumor microenvironment. The authors explained that collagen is the main component of the extracellular matrix in the tumor microenvironment and as such, regulates much of a cancer’s behavior. Among the primary cohort, the LNM rate was 16.4%.
In a validation cohort consisting of 143 patients with EGC, the LNM rate was similar, at 20.9%, a difference between the two cohorts which was not statistically significant, as investigators noted. On multivariate analysis, tumor differentiation was singled out as an independent predictor for LNM at an odds ratio (OR) of 4.5 (95% CI, 1.3-16.0; P=0.02).
Similarly, the depth of tumor invasion was also shown to be an independent predictor of LNM, at an OR of 6.7 (95% CI, 1.6-28.0; P=0.008). Importantly — and for the first time — the collagen signature of the tumor microenvironment also emerged as an independent predictor of LNM at an OR of 5.3 (95% CI, 3.0-9.3; P<0.001), the researchers stated.
They explained that two key features must be factored into the determination of the collagen signature of a tumor microenvironment.
“The first is the use of a suitable imaging approach to selectively visualize the collagen: Here, multiphoton imaging proved to be useful in helping visualize the collagen. Multiphoton imaging takes only about 5 to 10 minutes and is good at showing collagen,” Yan and colleagues said.
The second factor is the quantitative analysis of collagen from multiphoton imaging, and with these two factors, the team was able to see that the collagen signature of patients with LNM was significantly different from in patients without LNM.
Combined with the other two clinicopathologic features incorporated into the model, “we built a nomogram with good discrimination and calibration,” Yan et al. observed. “And our findings suggest that LNM is more likely to appear in patients with an undifferentiated histologic result, submucosal invasion, and a high collagen signature.”
Limitations of the study, the researchers noted, include the fact that it was done in Asia and that the findings need to be validated in western EGC patients.
Writing in an accompanying commentary, Jashodeep Datta, MD, and Vivian Strong, MD, both of Memorial Sloan Kettering Cancer Center in New York City, agreed that EGC requires accurate risk-stratification to identify tumors with a more aggressive biology, including the presence of LNM. This is because LNM in EGC is strongly associated with disease recurrence in patients undergoing gastrectomy, Datta and Strong explained, adding that positive lymph nodes are also associated with a higher risk of disease-specific death.
Importantly, however, “patients with T1a EGC are increasingly candidates for nonresectional interventions, such as endoscopic submucosal dissection, at expert centers,” the commentary noted. This is largely because the procedure is minimally invasive, preserves function, and results in better quality of life for patients.
In addition, as Yan and colleagues also noted, in order to be a candidate for the less-invasive procedure, patients must be at low risk to have LNM. When ECG is limited to the mucosa, this risk is less than 3%, but that increases to about 20% after the cancer has invaded the submucosa. Thus, “the accurate assessment of nodal status in EGC is integral to providing tailored surgical procedure,” Datta and Strong wrote, adding that the fact that the researchers validated the novel collagen signature as an important predictor of LNM in the setting of EGC is a key step forward.
“We congratulate the authors for their novel and important contribution to the field,” Datta and Strong stated, emphasizing, however, that the findings must now be validated in Western patients with EGC, as there may be differences in the biology of the disease between ethnic groups.
Yan and co-authors, as well as Datta and Strong, all reported having no conflicts of interest.