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Tumor regression patterns predict ypN positivity in advanced gastric cancer patientsA Tumor's Shrinkage Pattern Could Change Stomach Cancer Surgery

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Key Takeaway
Note that tumor regression patterns independently predict ypN positivity in advanced gastric cancer patients.

This cohort study evaluated 195 patients with advanced gastric cancer who underwent neoadjuvant or conversion therapy. The primary outcome was ypN positivity, analyzed according to tumor regression patterns: centripetal, diffuse/mixed, or centrifugal. A baseline clinicopathological model served as the comparator. The study utilized internal validation via a 7:3 stratified random split and 10-fold cross-validation to assess model performance.

Centripetal regression was associated with a ypN positivity rate of 5.4% (74/195 patients, 38.0% of the total cohort). In contrast, centrifugal regression was associated with a high ypN positivity rate of 75.6% (78/195 patients, 40.0% of the total cohort). Diffuse/mixed regression demonstrated an intermediate rate of 22.1% (43/195 patients). All comparisons yielded p < 0.001. Multivariable analysis identified diffuse/mixed and centrifugal regression as the strongest independent predictors of ypN positivity.

The full-cohort model demonstrated an AUC of 0.875, with a validation split-sample AUC of 0.826 (95% CI 0.826–0.922) and a pooled cross-validation AUC of 0.822. Model calibration was good, with a Brier score of 0.137. Safety data, adverse events, and tolerability were not reported in this study. The findings are observational; regression patterns are independent predictors rather than causal factors for nodal status.

Key limitations include the need for validated preoperative or intraoperative surrogate markers to explore the potential role in individualized lymphadenectomy, which requires prospective confirmation. These regression patterns are most appropriately used for postoperative risk assessment and multidisciplinary stratification rather than guiding immediate surgical decisions without further validation.

Imagine two people with the same type of advanced stomach cancer. They both get the same strong chemotherapy to shrink their tumors before surgery. After treatment, their surgeons see the tumors have shrunk significantly.

But one patient has a hidden, higher risk. The cancer is likely still lurking in their lymph nodes.

A new study reveals a surprising way to spot that risk. It’s not just if the tumor shrinks, but how.

Stomach cancer is a major global health challenge. When it’s advanced, standard care often involves chemotherapy first. This is called neoadjuvant or conversion therapy.

The goal is to kill cancer cells and make surgery more effective.

A huge question for surgeons is: how many lymph nodes need to be removed? Lymph nodes are tiny bean-shaped organs that are part of the immune system. Cancer often spreads there first.

Removing more nodes can ensure no cancer is left behind. But it also increases the risk of complications and longer recovery.

Doctors need a better map. They need to know which patients truly need extensive lymph node removal and which might do well with less.

The Surprising Shift

Traditionally, doctors looked at how much cancer was left in the main tumor after chemo. Less cancer was considered better.

But this study looked deeper. Researchers analyzed the pattern of shrinkage in the tumor itself.

They discovered three distinct ways tumors respond. And one pattern is a remarkably clear warning sign.

How a Tumor Shrinks Tells a Story

Think of the original tumor as a weed in a garden. Chemotherapy is the weed killer.

In some patients, the weed dies from the inside out. The center withers away while the outer edges hold on. Scientists call this centripetal regression.

In others, the weed dies from the outside in. The outer edges disappear, but the core remains stubborn. This is centrifugal regression.

The third pattern is a diffuse or mixed response, with patches of death scattered throughout.

Here’s the critical link. The way the tumor shrinks appears to mirror what’s happening in the surrounding lymph nodes.

The study, published in Frontiers in Medicine, analyzed data from 195 patients with advanced stomach cancer.

The results were striking. The shrinkage pattern was a powerful predictor of cancer in the lymph nodes after chemo.

Patients with centripetal shrinkage (inside-out) had a very low risk—only about 5% had cancer in their nodes.

Patients with centrifugal shrinkage (outside-in) had a very high risk. Over 75% had cancer in their lymph nodes.

The mixed pattern fell in the middle.

Even when accounting for other factors, the tumor’s shrinkage pattern was the strongest independent clue. Adding this pattern to other clinical data significantly improved doctors' ability to predict a patient's nodal risk.

But There's a Catch.

This doesn’t mean this treatment strategy is available yet.

The analysis was done after surgery, on the tumor that was already removed. For this to guide surgery, doctors would need to identify the shrinkage pattern before or during the operation.

That’s the next big challenge.

A New Framework for the Future

The researchers are clear. Right now, this finding is most useful for post-surgery planning. It helps oncologists understand a patient’s risk level and plan the next steps, like more chemotherapy, more precisely.

But it opens a door.

“This provides a framework for future research on individualized lymphadenectomy lymph node removal,” the study suggests. The ultimate goal is to find a scan or a test that can act as a stand-in for the shrinkage pattern, giving surgeons a real-time guide.

If you or a loved one is facing stomach cancer treatment, this research is a sign of progress toward more personalized care. It is not, however, a current standard of care.

You will not be asked about your tumor’s “regression pattern” before surgery today. The study is a retrospective analysis, meaning it looked back at old data to find a new signal.

Understanding the Limits

This was a single study with a moderate number of patients. Its findings need to be confirmed by other researchers in larger groups. The most important limitation is the timing: the pattern was seen in the final pathology report, not during surgery when decisions are made.

The path forward is about translation. Scientists must now work to find a “surrogate marker”—something visible on a PET scan, MRI, or through a blood test—that can predict the shrinkage pattern before surgery.

This would then need to be tested in rigorous clinical trials. Researchers would compare outcomes between patients who had lymph node surgery guided by this marker versus standard surgery.

It’s a promising road, but a long one. This study provides a crucial new map for that journey, pointing toward a future where stomach cancer surgery is tailored not just to the disease, but to how an individual’s unique disease responds to fight back.

Study Details

Study typeCohort
EvidenceLevel 3
PublishedApr 2026
View Original Abstract ↓
ObjectiveTo analyze the relationship between tumor regression patterns and ypN positivity and explore their implications for postoperative nodal-risk stratification after neoadjuvant or conversion therapy in advanced gastric cancer, while generating hypotheses for future individualized lymphadenectomy research.MethodsTumor regression patterns were classified as centripetal, diffuse/mixed, or centrifugal. Clinical and pathological characteristics were compared using the Kruskal–Wallis and χ² tests. Using ypN positivity as the outcome, a multivariable logistic regression model was constructed. Sensitivity analyses were performed in the subgroup with ≥16 retrieved lymph nodes, after additional adjustment for ypT and Becker tumor regression grade (TRG), and in the non-pCR subgroup. Internal validation was performed using a 7:3 stratified random split and 10-fold cross-validation. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), 95% confidence intervals, calibration, and the Brier score. We additionally compared a baseline clinicopathological model with a combined model incorporating regression pattern to assess incremental predictive value.ResultsAmong 195 patients, 74 (38.0%) exhibited centripetal regression, 43 (22.1%) had diffuse/mixed regression, and 78 (40.0%) demonstrated centrifugal regression. Centripetal regression was characterized by low PRI, higher LRI and CER, and a very low ypN positivity rate (5.4%), whereas centrifugal regression showed the opposite pattern and the highest ypN positivity rate (75.6%); diffuse/mixed regression showed intermediate features (all p < 0.001). Multivariable analysis identified diffuse/mixed and centrifugal regression as the strongest independent predictors of ypN positivity. The apparent full-cohort model demonstrated an AUC of 0.875 (95% CI 0.826–0.922) with good calibration and a Brier score of 0.137. These associations remained robust after additional adjustment for ypT and Becker TRG and in the non-pCR subgroup. Internal validation showed acceptable performance, with a validation AUC of 0.826 in the 7:3 split-sample analysis and a pooled AUC of 0.822 in 10-fold cross-validation. Addition of regression pattern to the baseline clinicopathological model improved discrimination and reduced prediction error.ConclusionPathological regression patterns provide effective stratification of residual lymph node metastasis after neoadjuvant or conversion therapy. Centripetal regression indicates a very low residual nodal-risk phenotype, whereas centrifugal regression is associated with a heavier nodal burden. At present, regression patterns may be most appropriately used for postoperative risk assessment and multidisciplinary stratification. Their potential role in individualized lymphadenectomy should be viewed as a future translational direction requiring validated preoperative or intraoperative surrogate markers and prospective confirmation.
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